The emerging impact of AI on recruitment

How is AI already affecting the recruitment process, and what can we expect to see in the future? AI-oriented tech company, IPsoft, provides an overview

What types of automation solutions are at the disposal of today’s recruitment teams? AI systems are already providing numerous options.

Traditionally, recruiters have often had to log into a system and manually identify the characteristics of ideal job candidates. With conversational AI, a recruiter can use natural language to ‘tell’ the system what type of candidate they are looking for, such as, ‘I’m looking for a compliance officer with at least five years of experience.’

Advanced AI systems can even generate relevant qualifying questions to further refine the search, such as those based on location or language proficiencies. Once the recruiter’s search has been created, the AI system will independently check through numerous candidate databases and job sites. As the system already knows the role requirements, only the most appropriate candidates are shared with the recruiter to take forward.

Augmenting effective recruitment from sift to interview

Talent acquisition is one of the key tasks for recruiters and one in which AI can play a transformative role. But there is no great need to change the way that candidates apply for jobs – ultimately, it’s augmenting the ability for recruiters to work effectively and build better relationships with prospective hires. Traditional recommendations for optimising CV and LinkedIn profiles to best highlight your skills and experience remain important – whether it’s an AI or human searching.

When it comes to the interview, AI software can also design interview questions that are personalised to the person’s professional competencies and experience. This approach helps both the candidate and recruiter: the candidate has the best opportunity to present and discuss their relevant experience and skills, in turn helping the recruiter make better and more informed decisions. It can also help to reduce unconscious bias in questions, as the AI can be trained to disregard certain information and guide the recruiter away from questions that could have previously exposed a candidate to bias.

Between the search for great candidates, the time needed to conduct interviews and the challenge in hiring top-tier employees, recruiting is very resource-intensive. Many organisations – including Hilton and Unilever – therefore already rely on AI to assist HR in the lengthy hiring process. From résumé screening to interviews, AI can help limit the amount of time it takes to narrow down the pool of job seekers.

Stepping towards the hybrid workforce

Recruitment, and indeed HR as a whole, involves many routine tasks, making this an area of potential improvement through the use of AI-powered automation. From the business perspective, freeing up recruiters and HR professionals from high-volume – but not necessarily high-value – tasks, can allow them to address more complex individual needs across the business and apply their skills to other projects, such as setting up a graduate training programme, building relationships with prospects, or researching and refreshing employee benefits schemes. Automation can help make these teams more productive, and ultimately make their jobs more interesting and rewarding.

In the long term, AI is going to fully automate tasks that human employees would rather not do, or simply do not have enough time to complete along with other, more important objectives. This is an important step towards the hybrid workforce, in which human and digital associates work alongside each other to help businesses scale faster with improved productivity and efficiency.

Covid-19 is becoming the accelerator for one of the greatest workplace transformations of our lifetime, with unprecedented changes in people’s day-to-day lives. What we are experiencing today could very well hasten this transition to a hybrid workforce and bring cognitive AI into the workforce even sooner than has been anticipated.

Johan Toll is Executive Director of Transformations at IPsoft, a technology company focused on AI, cognitive and autonomic solutions.

Weighing up the positives and negatives of AI

Akil Benjamin, Co-Founder and Head of Research at COMUZI, was a keynote speaker at AMBA & BGA’s Business School Professionals Conference 2019 in Vienna, Austria. Here, he delves into the ethical implications of AI and offers tips for leaders working with rapidly emerging technology

Could you introduce yourself and the main topics covered in your presentation at AMBA & BGA’s Business School Professionals Conference? 

I’m Head of Research at COMUZI, an innovation studio. We help people think about the future and build next-generation products, services and experiences, with a focus always on the people they are trying to serve.

The main topic of my presentation was consequence scanning; it was about asking AI the right questions. How we can demystify this technology? How can we make sure it gives us positive experiences? How do we amplify the positives while monitoring and mitigating the negatives? 

These days, AI can decide whether or not you get a mortgage; whether or not a judge should give you jail time. It can also help you out when it comes to your healthcare needs, and predict the sentence you are typing on your phone. It is becoming ubiquitous. 

Do the positives of AI outweigh the negatives?  

Yes and no. It depends which side of the coin you look at. AI is only as smart as the person or team that programmed, developed and designed it. So we have to start by thinking about how we design these things and then identify the positives and negatives from that. 

How can humans best work with this technology?

Technology has allowed us to do things much more rapidly. We can scan 300 million sources or candidates in a couple of minutes. It’s mind-boggling. But obviously, doing things this fast isn’t part of the human skill set. I believe that AI will show us the value of humanity: the things AI cannot do, such as making considered decisions, thinking about outcomes and taking time over things these are innately human skills.

What questions should we be asking AI? 

How does AI impact the people it has been programmed to serve? Does it achieve your number-one goal? In achieving this goal, does it serve to marginalise, hurt, or have unintended consequences for a secondary group of people? If so, who are these people?

Play devil’s advocate and start thinking about what the impact could be. Decisions are not irreversible but, with AI, they are usually longstanding and hard to unpick. Let’s do our best to limit the number of poor decisions that are made in the first place.

Where do you think AI does not or cannot add value? 

There will always be a need for human connections. I believe that AI is a tool, not a person; it facilitates doing something. As long as we stay connected and remember that AI is a tool rather than a proxy for human beings, I think we will be fine. 

What are the ethical implications we need to consider? 

Is AI reinforcing negative stereotypes or decisions? Is it reinforcing institutional divides or inequalities? Is it perpetuating injustices that people have been fighting over the past 20-100 years? 

If so, AI isn’t being used for the right thing. But, if we’re using AI to deconstruct and reimagine a carefully thought-out future, we are taking progressive steps. 

How can AI inform an authentic marketing strategy? 

Let’s demystify AI. It’s not magic in a box, it’s a programme. Let’s start telling people the truth and educating them through our marketing messages so they can participate in the conversation and come along with us. I think the better people understand the technology, the more they will be able to engage with it. 

In terms of how AI can influence marketing strategy, I believe it’s going to be another tool that we can leverage to gain a deeper insight into the messages we are putting out into the world. We might even get to the stage where AI is crafting that message. I should add that, to be ethical, we must be explicit about when we use AI technology in this way. People should know when they are talking to a computer and when they’re talking to a human.

What tips would you give leaders hoping to work with AI, to help them get started? 

Don’t be too slow, but don’t rush into anything either: AI isn’t a band aid, it won’t fix all your problems. Take the time to work out where it will be most beneficial when implementing it in your business. It’s a tool, a narrow tool; it can’t do everything, but it can do specific things well. So take your time to define the specific things you want to do well and what these look like.

Second, talk to people in the organisation, especially those who are directly involved in the problem you are trying to address. 

Third, ask yourself about the intended consequences of this, for the people you are looking to serve; keep reminding yourself that this is a tool and should not replace human relationships. Gather together people who can provide honest, unbiased perspectives. Having such people in the mix is important, especially when implementing powerful technology. ‘Yes men’ can be very detrimental to any project. 

Is education evolving fast enough to deal with the effects of AI on the future of work? 

No. The style of education, in my opinion, must change. Education needs to become more transactional. Currently, education is set up as a long-term investment: you set aside three years for a lifetime’s worth of learning. But with the world’s current rate of change, education needs to be more transactional. If I need to learn a specific core skill right now, I will need a 12-week course. In six months’ time, the technology may have changed. If I do enough of those courses I might gain a qualification;  or perhaps I’ll have a series of qualifications in specific things. I think that’s how education needs to direct itself. 

I would have had multiple degrees by now had I had the time to take formal qualifications in everything. I couldn’t afford to invest that time, I just had to learn what I had to learn and implement it. I think education has to evolve, recognising skills learned on the job as well as bringing in people who have acquired their skills in this way. 

How can artificial intelligence create value for business?

The Artificial Intelligence in Management (AIM) Institute at France’s Emlyon Business School is studying real-world issues facing organisations, in an interdisciplinary way. David Woods-Hale speaks to AIM’s Executive Director, Renaud Champion, to find out more

Artificial intelligence (AI) has been a talking point among Business School leaders for years, as institutions grapple with the most effective ways of preparing students to operate in the world of robotics. Renaud Champion, Executive Director of the AI in Management (AIM) Institute at Emlyon Business School in Lyon, France, tells us how his School is addressing the challenge.

What does your role as AIM’s Executive Director involve?

My mission is to design and implement the School’s AI strategy at every level, from research to pedagogical content and the development of digital tools. 

Given my background as an entrepreneur and an investor in AI and robotics, I have experienced how these technologies are already impacting companies dramatically, in terms of the way work is organised and done, and how they create value. The DNA of the Institute was therefore based around two main questions, which seemed both obvious and relevant from a Business School perspective: how can AI generate value; and how is AI impacting work and governance?

I developed the AIM Institute eight months ago, as a startup within the Business School, to galvanise interest in, and action around, this strategy. But to be successful, a good startup needs the right team, so involving recognised researchers in this ambitious initiative was a first key step. 

After only a few months and thanks to the work of the AIM Research Directors, Professor Ruthanne Huising and Professor Margherita Pagani, we already had 20 researchers from different backgrounds involved and were expanding quickly. We could also count on the involvement of Emlyon’s Scientific Committee, made up of leading academics from Stanford, Ecole Polytechnique Fédérale de Lausanne (EPFL), University of Texas at Austin, Vrije Universiteit Amsterdam, Florida State University and the University of Southern California, to help us. At this point, it was necessary for me to start working on initial outputs as well as ensuring AIM’s activities gained visibility. To this end, we created a series of seminars and research conferences for our various audiences, plus new pedagogical modules for our students.

What disruptive trends are you observing around AI and its impact on higher education and work?

Our aim at the Business School is to prepare tomorrow’s managers and leaders to work in a technology-driven world. At the same time, it is also the responsibility of each manager – not just of the chief operating officer or chief technology officer – to ask themselves: ‘How can AI help me do my job more efficiently or differently?’

But to do this, managers need to be trained in these technologies, in design thinking methodologies, agility and so on. Companies need to invest in AI but also in their own people to get the most out of these technologies. This is why Emlyon includes courses on data, robotics and machine learning, and on the impact of these technologies on companies, in all its programmes.

It is important for us, as a Business School, to ensure our programmes are increasingly hybrid. However, AI is also transforming pedagogy itself. We are building new AI-augmented tools to support our students in their lifelong learning journey. Digital can help us personalise that experience.

Can you provide some background to the launch of AIM?

Over the past 20 years of working and investing in AI and related technologies, I have been involved in several different projects impacting various markets and sectors, from finance and agriculture, to transport and healthcare. 

This experience convinced me that AI is not only an economic opportunity, but also a social opportunity, because it can add value by putting humankind back at the heart of things. Researchers, engineers and product managers must be trained to become ever-more ethically responsible when they design, deploy or use emerging AI technologies. These principles are at the core of the AIM Institute. Our ambition is to understand the world in its complexity; build knowledge from it by taking an interdisciplinary approach, and disseminate this to various audiences in adapted formats, with the use of an omnichannel pedagogy. 

Why are there so few empirical studies looking at how AI will impact the workplace?

I believe the reason why there are many predictions about how AI will change business and the way we work, but relatively few empirical studies, is mostly due to companies’ late appropriation of recent AI-driven technologies which are still seen as not being mature enough. 

Most companies are still in the middle of their digital transformation and it is difficult for many to look ahead to the AI revolution. But it is coming, and it’s already affecting sectors such as healthcare and transport. Our first goal within the Institute is to work with companies on real-world problems and to support grounded, empirical studies of the way AI can create value around a broad range of business issues, as well as how this technology is changing what it means to work and the way work is organised, done and rewarded.

Can you talk us through the AIM Institute’s priorities of research, innovation and dissemination?

We aim to understand the opportunities and implications of AI for managing organisations, industries and business ecosystems. With this in mind, we have launched several series of seminars and workshops with leading scholars from around the world to address questions exploring the impact of AI on work and value creation, and organise monthly outreach lectures, open to the public, about the technologies behind AI in order to demystify and educate broadly.

On the pedagogical side, we have created an online certificate in AI and business for managers, new courses within our fields of expertise to be integrated into all of Emlyon’s programmes (at bachelor’s, master’s, MBA, and executive education levels), and post regular presentations on the School’s YouTube channel.

How complex is this type of implementation for Business Schools operating in a constantly changing and disrupted tech environment?

As in any other industry, in education we need to adapt constantly and cope with the latest technological breakthroughs. This requires a high level of agility around understanding technologies and being able to anticipate their impact, and this includes identifying the business and organisational issues that could emerge. Our approach is strongly interdisciplinary, so we address different variables across marketing, strategy, sociology and ethnography, alongside technology and ethics.

By building innovative pedagogical solutions based on digital and AI, we are questioning Emlyon’s mission as a School. All these new functionalities challenge the role of the professor. What can algorithms optimise and what should stay in the hands of the teacher? The question of how technology can be used to complement human skills also needs to be tackled in our domain of higher education.

How does your initiative work in practice and why is this a good example of how Business Schools and employers can work collaboratively to address issues such as AI?

On the research side, we have several studies under review by top academic journals and are working on new projects studying human-machine interaction; the impact of smart devices on the supply chain and operations; new business models derived from AI-augmented digital platforms, and how to design and create better user experiences through interactions with new technology.

These projects are interdisciplinary and address real business issues faced by organisations. Working closely with employers in an empirical way is a methodology we favour in order to anchor our actions in the real world. It means we can guarantee that we are relevant and impactful when disseminating this knowledge through pedagogy. We are also working on the creation of our technology transfer department. For every research project, we consider whether the work has the potential to contribute to our understanding of how organisations and institutions can take meaningful and responsible advantage of AI. For example, where we identify projects that have concrete business applications, we could develop patentable models that could be coded and used to develop an application that a partner organisation might find useful. Alternatively, we might explore the possibility of launching and supporting a startup to build on this innovation.

What are the implications of AI for labour markets, organisational design and governance and how can the AIM Institute make an impact here?

Thanks to embedded AI, robots are becoming more intelligent and can work safely alongside human workers. Machines will complement people in the workplace rather than competing with them, and this combination will speed up processes, make things easier for humans and enable people to add human value. 

For instance, in automotive factories 10 to 15 years ago, there were huge industrial robots operating behind security fences. But now the robots are becoming more intelligent and are being taken out of cages. Humans are back on the production line and are now operators of robots. From a business perspective, AI can help workers by automating dull, difficult, dangerous, or repetitive tasks.

In addition, AI-augmented systems, when combined with human operators, are always more efficient than human experts alone, or even machines alone. There is a healthcare study which shows that AI analysing a patient’s tumour will not perform as well as a human doctor. But if you combine the human doctor with an AI algorithm, the analysis is a lot more effective. 

AI can also be helpful in providing other diagnostic information that doctors can use to make better decisions about patient care. It won’t just be the healthcare sector that has to manage this balancing act, all areas will be affected.

Companies have no choice but to adapt and identify how they can use these technologies for their benefit, from both an economic and people perspective. Some jobs will disappear while new ones will be created. 

But rather than focusing on the numbers on each side, I think we need to understand how the whole structure of employment is being transformed by AI: most jobs won’t disappear, they will evolve. This is exactly what the AIM Institute is looking at: understanding how AI will transform the way organisations operate, how they are governed and how they recruit.

Your goal is to create and implement practical solutions from the research – what format will these take?

Everything starts with research. Through our research projects, we generate knowledge. This knowledge will be published in respected academic journals, but it is also the raw material with which we can develop our teaching. 

To do this, we will need to translate the research projects and findings into pedagogy, and this requires some engineering. When we talk about innovation within the AIM Institute, it is used first and foremost (but not only) from a pedagogical perspective. 

The technology-transfer mechanism, which is most often used in technical universities to build on their research, is something we want to implement. It might not always be possible, but our goal is for the team to consider each opportunity in turn, and in connection with our corporate partners as and where appropriate. 

What are the next steps?

We are now entering an acceleration phase and looking to expand globally – first into central and east Asia and Africa, where 

Emlyon Business School already has a strong presence, and then into India. We are also recruiting post-doctorates and assistant professors to open up new fields of knowledge around AI’s impact. 

We are also finalising online certificates and designing new courses for students. Last but not least, we are working on a new series of seminars, conferences and workshops for the coming academic year. It is an exciting time for us, working on a very exciting subject.

Renaud Champion is the Executive Director of the AI in Management (AIM) Institute and Director of Emerging Intelligences at Emlyon Business School, France. He is also Director of euRobotics AISBL, the European Association of Robotics. 

Using AI to empower the next generation

MIP Politecnico di Milano has developed an AI-infused career-coaching tool to help students gain new skills faster and boost their employability, explains Federico Frattini

As the education sector booms, universities are being forced to think further outside the box to attract the best students. Courses that are not flexible, personal and relevant to the increasing digitisation of many jobs and workplaces are simply being left behind. New demands from students about how courses are taught, as well as their content, are making the industry increasingly competitive and put more pressure on the educational systems in place. The goal for students is not just to graduate, but to be truly employable, by gaining a set of skills that will be relevant now and in the workplace of the future.

Practically all universities will have witnessed the market widening over the past few years, with a new demographic of potential students looking to continue their lifelong learning and keep abreast of ongoing technological advances. The World Economic Forum reports that 65% of  primary school students will be doing jobs that don’t yet exist when they graduate. 

From this perspective, acquiring new skills is important, not only for young people, but also for those wishing to remain competitive in their industry and grow in their professional life or even in their current position. In fact, according to Vanessa Byrnes, Sector Managing Director at global talent management consultancy, Alexander Mann Solutions, upskilling has never been more vital. She explains: ‘In our experience, retraining and redeploying internal resources is one of the most efficient ways of bridging future skills gaps. When faced with the option to “buy, build or borrow” expertise, growing your own talent comes with numerous benefits, not least the retention of culture and reduced recruitment costs.’

A career coach for students and alumni

Fresh technologies must be made available to empower everybody with new capabilities. Research suggests that AI, as well as a plethora of other new technologies, will directly impact a huge number of jobs worldwide, so real-life experience is critical in both understanding and adapting to these advances. For MIP Politecnico di Milano, using these new tools is important both for our School and our students. 

That’s why we have launched FLEXA, an AI continuous learning platform which acts as a career coach for potential students, current cohorts and alumni networks. 

The basic idea is to give our students the knowledge they need to achieve their career goals faster and make them more employable. Developed in partnership with Microsoft, FLEXA analyses each individual and suggests personalised material that can close skills gaps while promoting their profiles to recruiters. 

So, how does it work? To begin, users undergo a short assessment of their hard, digital and soft skills. This, combined with details of their personal career aspirations, helps to identify courses, tutorials, digital material, MOOCs, and even the best mentors and coaches to help enhance their capabilities. 

FLEXA can be accessed by current students, alumni and potential students alike, mapping out their next logical steps to close skills gaps at all levels of their career. Each individual’s data is then set against job skills required by the market and FLEXA allows a number of top recruiters to access the profiles of both students and alumni. 

FLEXA uses Microsoft’s cloud service and AI platform, Cortana Intelligence, which Silvia Candiani, Microsoft Italy’s General Manager describes as an ‘innovative continuous learning tool’. She says it is ‘fully aligned with Microsoft’s culture of continuous skills updating and its mission of empowering every person and organisation on the planet to achieve more. The goal is upskilling, the improvement of people’s employability, and (for it to act) as an enabler of innovation and digital transformation’.

Personalisation of the student experience 

Innovations such as these are the first step in accelerating a transformation in education. Matching curricula with aspirations is one side of the coin, but it becomes a larger, more targeted operation when employers get involved. This creates the perfect platform to match supply and demand, and provides critical information to fine-tune curriculum development. This is likely to transform the curriculum from a top-down, education system-led model to a bottom-up, or market-led one, while still working on students’ terms. 

One of the key benefits of this digital learning ecosystem is that it allows users to personalise their learning journey, which is of increasing importance for those selecting which MBA or master’s degree to undertake. The changing role of Business Schools means they must now curate knowledge and broker content, to deliver to students and alumni at exactly the right time for them and their careers. It appears that management education is becoming less about imparting ‘know-how’ to the next generation of business minds than focusing on ‘know-where’ – the critical ability to source knowledge from different media. FLEXA is designed to do just that.

The implications of using technology such as FLEXA are far-reaching. One advantage is the wealth of data that can be collected from recruiters using the technology, many of which systematically develop talent for future roles. As Byrnes explains: ‘In order to know what skills need to be developed to ensure an organisation is future-fit, leaders need to map capabilities against project demand.’ 

In this way, data collected from the system will provide insights into what employers are really searching for, as well as the knowledge that allows students to reach career targets. This is invaluable for the education system, which can start to anticipate and follow shifting demands in the real business world for the first time. This could be the key to understanding how to close rapidly growing, global skills gaps. This service could even be offered without an accompanying degree to strengthen the digital capabilities and soft skills of individuals, whether they are a Business School student or not. This is an indication of potential societal impact.

In addition, the system also encourages intelligence-based networking between individuals, allowing collaborative learning and skills building, as well as connecting people with mentors. This is a huge advantage to students who are exposed to situations where they must develop soft skills such as problem solving, verbal communication and adaptability. 

According to Deloitte’s 2016 Global Human Capital Trends report, executives now consider these skills key to employee retention, improving leadership and building a meaningful culture. In fact, 92% of Deloitte’s respondents rated soft skills as a critical priority. As technologies such as AI and robotics are increasingly capable of completing automated and analytical tasks, business minds of the future must develop their ability to work effectively alongside and in synergy with these systems, as well as nurturing the qualities that tech does not possess. 

Growth of online education and the need for flexibility 

The number of online courses being offered by Business Schools is increasing, as is the number of applicants to them. A 2018 report published by the Babson Survey Research Group suggests that the number of US students who enrolled in at least one online course
rose by 5.6% between 2015 and 2016, a faster rate than the three previous years. Jeff Seaman, Co-Director of the Babson Survey Research Group and a co-author of the study, expects this trend to continue and that data for 2017 will mark 15 consecutive years of enrolment growth. At MIP, flexible learning with the student at the core of the programme is part of the School’s ethos. In the past few years, we have been experiencing a radical change in the needs of professionals interested in post-graduate training who, besides an increasing need for flexibility and the compatibility of educational programmes with their agenda, are demanding a highly personalised and concrete learning experience. MIP has responded to this need with a dedicated educational offering revolving around the concept of smart learning, which combines digital learning tools with personal coaching, mentoring and advisory services. 

In 2012, the School started to adopt emerging technologies in higher education and  its first digital executive MBA was launched in 2014. It was so successful that we had to launch a new edition of the programme every six months. Today, there are domestic and international executive MBA digital offerings, the Flex and International Flex Executive MBAs, which allow participants to decide where and how to access their lesson material, from anywhere in the world and with any device. This means that their learning fits around other commitments, and is part of the School’s wider digital strategy to use tech to enhance learning capabilities. In 2016, the Flex EMBA was shortlisted for the MBA Innovation Award in the annual AMBA Excellence Awards. FLEXA further enhances the School’s educational offerings and operates entirely online, making it accessible to all users at any time.

Advances in technology mean the traditional education framework will soon become as anachronistic as the notion of knowledge acquisition occurring merely through a textbook, or in a discussion. The best people in each field are becoming aware that they must keep up with these advances and know how to use them to get ahead, as well as developing soft skills. If Business Schools don’t innovate and cater to this growing demographic, they are likely to see potential students applying elsewhere. In order to remain valuable, Business Schools must rise to the challenge of engaging alumni in a meaningful way, and encourage them to see the value in lifelong learning. By failing to take advantage of new technologies, universities are not arming current – or future – generations of business minds with the knowledge and skills needed to succeed.

Federico Frattini is Associate Dean of Digital Transformation at MIP Politecnico di Milano.

Winning at interview and preparing for AI-infused recruitment

If your CV was good enough to get you an interview, that’s great, but looking good on paper is just the starting point. At interview, you have to demonstrate that you have the skills to do the job and will be a good fit with the team.

Your audition

An interview is an audition – your opportunity to shine and prove you are the perfect person for the role. The actor Harlan Hogan is famous for delivering the catchphrase, ‘you never get a second chance to make a first impression…’ and it certainly pays to be well prepared.

The interview is not, however, just an exercise in self-promotion. The hiring manager has a specific brief and, in effect, you are there to convince the interviewer that you can solve their hiring problem. An interviewer will focus on gaining an understanding of you and your motivation and how these fit with the role, existing team and organisational culture.

Be prepared to show how you will add value and that you are the best candidate to help the organisation succeed. When you are asked to tell the interviewer about yourself, what this request really means is that you should show ‘what value would you bring to us?’

Thorough preparation and the way in which you present yourself are crucial to success; but, since performance at interview is not a reliable indicator of job performance, interviews these days tend to be quite structured and often concentrate on competencies with targeted behavioural questions.

The basics

Clarity and brevity are your touchstones. Show you are articulate and able to think on your feet while communicating effectively under pressure. Be ready to provide work-related examples that show your personality and how you operate and illustrate that you will be a good fit in the role. Ensure you pinpoint your strengths and expertise and emphasise your points with examples that showcase your achievements. Show how you will make a real difference when you are appointed.

You may be asked some tricky questions as interviewers probe to assess how you react. Keep your answers concise and relevant. You are likely to be asked competency-based questions relating to your previous roles, so make sure you have plenty of examples prepared.

Employability skills are also an important factor for success at work and showing that you have these skills and focusing on them during the interview process, along with your technical expertise, will help differentiate yourself from the competition. Concentrate on showcasing good communication skills, commercial awareness, a commitment to lifelong learning, problem-solving skills, and professional manner and attitude.

Demonstrating your skills at interview is not easy and we all have ‘off days’ but interview practice will help. If you can, get a friend, colleague, career coach or mentor to help with some sessions to rehearse your responses, improve your confidence and hone your performance.

The changing face of recruitment

HR now use robotics to enhance and expedite the recruitment process and leave hiring managers free to concentrate on more complex tasks. AI is supposed to remove human biases that adversely affect some candidates and it seems that nearly all Fortune 500 companies are using some form of automation to enhance hiring processes.

It’s interesting to consider what changes job seekers are likely to see as robots are used in the interview process more often. A large Swedish recruitment specialist, TNG, has been experimenting with such a system to offer candidates job interviews that are free from the unconscious biases that managers and recruiters may bring to the hiring process. The idea is to make the experience ‘seem human’ while ‘background-blind’ AI programmes manage tests and perform initial online interviews.

The robot interview doesn’t indulge in pre-interview small talk and asks all questions in an identical way, in the same tone, and typically, in the same order. This is believed to create a fairer and more objective interview. Recruiting managers are then provided with transcripts of the interviews so they can decide which candidates to move to the next stage of the process, based on their answers alone.

Impressing the algorithm

Interviewees can’t relax too much in this context as the AI programme records and analyses responses, and where there is a video interface, monitors facial expressions. Some candidates will find they are comfortable with such an interview, as they will perceive it as a non-judgmental, non-threatening and non-invasive means of interaction which affords them scope for presenting themselves in a relaxed manner. Others may find talking to a screen and recording their answers more challenging.

There is some discussion around the issue of bias and AI. After all, the algorithms at work here are programmed by people who have flaws, biases and preconceptions that are all too easily inherited by an AI system. That said, many candidates seem happy with these developments. Randstad, a Dutch multinational recruitment firm, found that a majority of US job candidates believe technology, AI included, has made applying for jobs more efficient. These same candidates also felt more respected and engaged in the recruitment process as they received automated updates.

Impressing a robot at interview may require candidates to adjust their focus. Answering questions that will be analysed by an algorithm means your responses must focus on the job specification, using words and phrases directly related to the role. You cannot rely on building rapport with the interviewer because a robot is not interested in bonding with you. It will still be important to be well prepared for the interview, having read not just the job description but also the organisation’s website information to see what qualities they prioritise and the culture they portray.

The plain fact is that a robot can interview many more candidates per day than a person can and will also review a candidate’s social networking activity thoroughly and quickly. At least in the early stages of the recruitment process, we are likely to see automated AI powered systems being used as a matter of course. Whether the interviewer is human or machine it remains important that the applicant makes a good impression.

Liz Sebag-Montefiore is a Director and Co-Founder of career management firm, 10Eighty and has provided HR solutions to a wide range of industries since 2005.

Is AI making dangerous decisions without us?

Artificial intelligence (AI) is set to take control of many aspects of our lives, but not enough is being done with regards to accountability for its consequences.

The increasing application of AI across all aspects of business has given many firms a competitive advantage. Unfortunately, its meteoric rise also paves the way for ethical dilemmas and high-risk situations. New technology means new risks and governments, firms, coders and philosophers have their work cut out for them.

If we are launching self-driving cars and autonomous drones, we are essentially involving AI in life-or-death scenarios and the day-to-day risks people face. Healthcare is the same; we are giving AI the power of decision making along with the power of analysis and, inevitably, it will have some involvement in a person’s death at some point in the future, but who would be responsible?

Doctors take the Hippocratic oath despite knowing that they could be involved in a patient’s death. This could come from a mistaken diagnosis, exhaustion, or simply missing a symptom. This leads to a natural concern about research into how many of these mistakes could be avoided.

The limits of data and the lack of governance

Thankfully, AI is taking up this challenge. However, it is important to remember that current attempts to automate and reproduce intelligence are based on the data used to train algorithms. The computer science saying ‘garbage in, garbage out’ [describing the concept that flawed input data will only produce flawed outputs] is particularly relevant in an AI-driven world where biased and incomplete input data could lead to prejudiced results and dire consequences.

Another issue with data is that it only covers a limited range of situations, and inevitably, most AI will be confronted with situations they have not encountered before. For instance, if you train a car to drive itself using past data, can you comfortably say it will be prepared it for all eventualities? Probably not, given how unique each accident can be. Hence, the issue is not simply in the algorithm, but in the choices about which kinds of datasets we use, the design of the algorithm, and the intended function of that AI on decision making.

Data is not the only issue. Our research has found that governments have no records of which companies and institutions use AI. This is not surprising as even the US – one of world’s largest economies and one that has a focus on developing and deploying AI – does not have any policy on the subject. Governance, surveillance and control are all left to developers. This means that, often, no one really knows how the algorithms work aside from the developers.

When 99% isn’t good enough

In many cases, if a machine can produce your desired results with 99% accuracy, it will be a triumph. Just imagine how great it would be if your smartphone can complete the text to your exact specification before you’ve even typed it.

However, even a 99% level of precision is not good enough in other circumstances, such as health diagnostics, image recognition for food safety, text analysis for legal documents or financial contracts. Company executives as well as policymakers will need more nuanced accounts of what is involved. The difficulty is, understanding those risks is not straightforward.

Let’s take a simple example. If AI is used in a hospital to assess the chances of patients having a heart attack, they are detecting variations in eating habits, exercise, and other trends identified to be important in making an effective prediction. This should have a clear burden of responsibility on the designer of the technology and the hospital.

However, how useful that prediction is implies that a patient (or her/his doctor) has an understanding of how that decision was reached – therefore, it must be explained to them. If it is not explained and a patient [that is given a low chance of having a heart attack] then has a heart attack without changing their behaviour, they will be left feeling confused, wondering what the trigger for it was. Essentially, we are using technical solutions to deal with problems that are not always technical, but personal, and if people don’t understand how decisions about their health are being made, we are looking at a recipe for disaster.

Decision making, freedom of choice and AI

To make matters worse, AI often operates like a ‘black box’. Today’s machine learning techniques can lead a computer to continue improving its ability to guess the right answer or identify the right result. But, often, we have no idea how the machines actually achieve this improvement or ‘learn’. If this is the case, how can we change the learning process, if necessary? Put differently, sometimes not even the developers know how the algorithms work.

Consumers need to be made more aware of which decisions concerning their lives have been made by AI, and in order to govern the use of AI effectively, the government needs to give citizens the choice of opting out of all AI-driven decision making altogether, if they want to. In some ways, we might be seeing the start of such measures with the introduction of GDPR in Europe last year. However, it is evident that we still have a long way to go.

If we are taking the responsibility of decision making away from people, do we really know what we are giving it to? And what will be the consequences of the inevitable mistakes? Although we can train AI to make better decisions, as AI begins to shape our entire society, we all need to become ethically literate and aware of the decisions that machines are making for us.

Terence Tse is an Associate Professor of Finance at ESCP Europe Business School and a Co-Founder of Nexus FrontierTech, which provides AI solutions to clients across industries, sectors, and regions globally. His latest book, The AI Republic: Building the Nexus Between Humans and Intelligent Automation is due for release in June 2019.

Exploring the digital marketing revolution

To create and communicate superior customer value, marketers must now combine traditional advertising with social and digital tools, argues American marketing guru Philip Kotler, in an interview with David Woods-Hale

You’ve written Marketing 4.0? What has changed since Marketing 3.0 was published in 2010?

Marketing is undergoing a digital revolution. We published Marketing 3.0 seven years ago to help companies broaden their view of how computers and the internet impact marketing theory and practice. We stressed the importance of meeting the needs of women, young people, and ‘netizens’ in carrying out company marketing activities. 

Today there is a need to pay attention to the growing role of social and digital media. Social media – such as Facebook, Instagram, Pinterest and Snapchat – create an increasingly connected world and they stimulate greater communications and sales to a wider world. Digital media is enabling artificial intelligence (AI) and the ‘internet of things’ (I0T) and increasing the rate at which robotisation and automation is penetrating business. Our aim in Marketing 4.0 is to illustrate the growing role and impact of digital marketing. I’ve also described this ‘new marketing’ in my 15th edition of Marketing Management

How can Marketing 4.0 help in bringing marketers up to date with the current skills required – from traditional to digital?

In the past, consumers made purchase decisions largely in retail outlets, whether in an auto dealership or in a large department store. Some consumers also used the telephone or mail order catalogues. Today, a growing number of consumers are making more of their purchases online via online retailers. In-store retailing is facing a major decline: witness, in the US, the news of Macy’s closing many stores, clothing store The Limited going out of business and shopping centres in deep trouble. 

Consumers still go into stores to sample and touch the product and then use their smartphone to see if they can a better deal elsewhere. Many retail shops are evolving into ‘showrooms’, partly charged by the company to its advertising budget. Business-to-business transactions are being increasingly conducted with digital media. Most companies list their product catalogues on the internet. Purchasing agents are happy to compare prices on the internet and are less interested in accepting sales calls. All this points to the need for companies to acquire social and digital skills before they are outclassed by more sophisticated digital competitors.

You describe ‘shifting power dynamics’ in the market. Can you explain this in more detail? 

Power has been shifting from the advertising giants who used 30-second commercials to inform and persuade consumers, to savvy consumers – who rely on their friends and acquaintances, plus online product ratings, to make their brand choices. Power has moved from companies to consumers. Companies must now develop fresh pictures of how consumers journey toward making their final purchases. It’s no longer a journey from a 30-second commercial to a purchase but from a stimulus on the internet, or from a friend, to a search for further information, to a purchase. Marketing 4.0 discusses the key steps in consumer journeys and the various touch points that will have an impact on the final purchase decision.

You explain how the rules of marketing regularly change, but this time the very customers have changed – and this is revolutionary – can you talk a bit more about this?

The basic maxim of marketing hasn’t changed. Decide on the consumer need your company wants to meet and the individuals who strongly have this need. Create a solution that meets this consumer need better than any competitor can meet it. See your job as one of creating superior customer value and communicating this value in a superior way.

What is revolutionary is the need for the company to incorporate social and digital tools to carry out this work. Companies need to collect ‘big data’ about individual consumers who have specific needs and apply sophisticated marketing analytics to arrive at consumer insights that can be converted into compelling consumer value propositions.

How do cyclical trends in the economy affect marketers? More specifically, if demand-led growth is on the decline, what single marketing effort is the most important to avoiding a loyal consumer defecting to a competitor?

Buyer behaviour obviously changes in times of market growth versus market decline. When a recession, or a fear of recession, occurs, consumers will intelligently reduce their expenditure and move towards lower-cost products. Every competitor will have a choice: increase the value of the offer, or cut the price of the offer. Normally it makes sense for the company to retain the price and better document and confirm the offer’s superior customer value. If superior value doesn’t exist, the company either has to add more value (for example, free shipment) or cut its price.

Do you think the original elements of the traditional marketing mix will still be relevant in 10 years’ time? 

The marketer’s main toolkit remains the 4Ps (product, price, place, and promotion) and STP (segmentation, targeting, positioning). Each of these elements undergoes modernisation all the time. Product includes packaging, as well as service products. Place is being redefined into omni-channel marketing but it is still place. Promotion is including digital and social communication alongside print and broadcast media. I would welcome a new marketing framework if it promised to address marketing decision problems in a more decisive way. Until then, most companies will use the traditional framework in preparing their marketing plans.

How will creative and media agencies need to evolve over the next five years to keep up with the pace of technology? 

The agency of the future will develop skills in both traditional and digital advertising. This would be better than hiring separate traditional and digital agencies because companies must connect traditional and digital advertising. A 30-second commercial may need to include a digital address showing where viewers can go for more information. The job of the ‘full-service agency’ is to find synergies between the two types of communication, so that 2 + 2 = 5, not 4.

Do you think that the chief marketing officer (CMO) role will be replaced by a combination of chief tech officer and chief analyst, or is this still a viable career path?

I’d like the CMO position to continue to manage the integration of all the elements that will impact on customer demand. The CMO should spend at least 50% of their time working with the other ‘chiefs’ in the company. The real value of the CMO will be realised when he or she is included in all the strategy planning. It would be unwise to confine marketing to designing tactical moves. The CMO is in the best position to foresee where the particular market is going economically and technologically. The CMO’s staff must include an excellent digital person and technology person. 

Do you think marketing and HR may evolve into one business function, as people leadership and organisational branding become increasingly connected, with shared goals and purposes?

I would prefer the heads of marketing and HR to work very closely together but remain separate functions. The CMO is highly interested in seeing that HR hires very service-minded people. In the hotel business, Marriott says that the first job is to hire the right employees and then the customers will come. The CMO should support the HR person to gain a sufficient budget to hire excellent employees, not just average employees. The evidence is strong that excellent employees have a productivity impact that is several times that of average employees.  

Do you think that zero-based budgeting for marketing, based on the Unilever example, will be widely adopted, to make marketing entirely accountable? How can value be measured throughout all channels since tracking is harder offline? 

Zero-based budgeting for marketing means starting each year with no budget allocated to marketing, until marketers propose specific marketing spend – along with the evidence that results will exceed costs. This is in contrast to normal budget setting where the budgets of the past year are the starting point, raised or lowered slightly. We acknowledge that some past marketing expenditures were not productive, and that from time to time, it is worth reviewing each major budget item to decide whether it should be eliminated, decreased or increased. 

The problem with zero-based budgeting for marketing is two-fold. Many campaigns need continuity and they shouldn’t be cut off before they have achieved their full impact. 

Also, it is increasingly difficult to assess the financial impact of a particular digital tool or a particular marketing channel in an increasingly complex and interactive world. 

Zero-based budgeting is a highly impractical tool for yearly budgeting. However, I grant that it could raise marketing efficiency by being introduced every few years.

Do you believe leaders across all disciplines and functions need to change their mindsets to succeed in a volatile world? 

Today’s world is increasingly characterised by volatility, uncertainty, complexity, and ambiguity (VUCA). Donald Trump’s election as US President has greatly contributed to VUCA. If Hillary Clinton had been elected (she won the popular vote by 3 million votes), we would arguably not be in a VUCA world. Events would have taken their normal course and businesses would carry normal expectations. 

But Trump sends out tweets in the middle of the night, many of which attack companies, journalists, judges, pollsters, or the voters themselves. These attacks are a sign of paranoia. Many business leaders have to think twice about any move for fear that the president will call them. Consumers are worried about their health benefits and they are no longer certain about social security and Medicare. They, and businesses, are spending their money more carefully, which slows down economic growth.

My answer to that? Business leaders must change their mindsets, in light of Trump’s erratic behaviour; he issues executive orders almost daily. His behaviour has been copied by populist leaders abroad with the effect of introducing even more instability into the world economy. 

Are there marketing skills that all MBA students and graduates need to thrive in a VUCA business world?

Most Business programmes are training their students in social and digital skills. They are also making students more aware of the effects of climate change. Professors are increasingly criticising shareholder value as the measure of business success and replacing it with stakeholder value as a more comprehensive measure of business performance. Marketing students graduate with a broader view of the factors that affect corporate image and reputation than previous Business School graduates. 

And finally, do you feel optimistic about business adaptability as the
world becomes more uncertain but also more connected? 

Business literature increasingly emphasises company agility and responsiveness to rapidly changing conditions. Companies need to monitor technological trends, political debates, and economic issues. Companies such as Unilever, Starbucks and Amazon show incredible business adaptability. But many companies are still coasting and need a few more shocks to wake up. My hope is that an increasing number of companies recognise that growing income inequality will hurt, not help them, and that they need to take a more expansive customer benefit and welfare view of what makes an economy strong.

Philip Kotler is the SC Johnson & Son Professor of International Marketing at the Kellogg School of Management, Northwestern University, Evanston, Illinois

Professor Kotler received his Master’s Degree at the University of Chicago and his PhD Degree at MIT, both in economics, conducting post-doctoral work in mathematics at Harvard University and in behavioural science at the University of Chicago.

He is the author of 57 books and has published more than 150 articles in leading journals. He was the first recipient of the American Marketing Association’s ‘Distinguished Marketing Educator Award’ (1985) and has received a host of other accolades, being inducted into the Management Hall of Fame in 2013. 

Kotler has consulted for such companies as IBM, General Electric, AT&T, Honeywell, Bank of America, and Merck in marketing strategy and planning, marketing organisation and international marketing. He has travelled throughout Europe, Asia and South America advising companies on applying economic and marketing science principles to increase competitiveness, and governments on developing the skill sets and resources of their companies for global competition.

He has been Chairman of the College of Marketing of the Institute of Management Sciences, Director of the American Marketing Association, is a member of the Board of Governors of the School of the Art Institute of Chicago and of the Advisory Board of the Drucker Foundation. 

He has received a number of honorary doctoral degrees from several international organisations.  

How to get the best out of artificial intelligence

Artificial intelligence-driven technology will be transformational in many industries, but how it shapes organisations will depend on their leaders, writes Jonathan Knight

Much has been written – not all of it true – about the impact that artificial intelligence (AI) will have on the workplace. 

AI is already transforming automated industries, including production, e-commerce, advertising, finance and logistics. It will soon impact more analytical and advisory occupations such as law, consultancy and medicine. But media reports about AI sometimes paint an unrealistic picture of its powers and fail to allow for obstacles in its application. 

There has been less discussion of the practical impact AI will have, or how its application may be slowed due to poor public acceptance. Nevertheless, despite uncertainty about the breadth and pace of its impact, it is certain that AI will create significant challenges for leaders. 

AI – how far will it go?

A fascinating five minutes can be spent taking the BBC’s test to ascertain how likely robots are to take over your job in the next two decades. With the ability to analyse enormous quantities of data, perform intricate operations and recognise instructions, the direction of travel is clear: AI-driven technology will be transformational in many industries. 

Needless to say, however, AI is not magic. Virtually all recent progress in machine learning has been made through ‘supervised learning’, in which input data (A) generates a straightforward response (B). Human intelligence is capable of much more than A to B; we make choices based on complex data gathered over the course of our lifetimes, through learning, memory, experience and genetics. And, given the limitations of present-day AI, robots are a lot less likely to assimilate certain skills in the near term; those, for example, that require an understanding of history and culture, or context and reason. 

It is difficult to imagine robots developing the empathy of humans, which is why we are more likely to be comfortable with a robot carrying out a complicated medical procedure on us, than with a robot checking up on us post-surgery to see how we’re doing and to offer us a cup of tea. 

In other words, while tasks that require complex technical skills and knowledge may be carried out by robots, there are some that we would rather were done by other human beings, with whom we can have genuine, human emotional interaction.The ability to exercise effective judgement, creativity and discretion, combined with the capacity to improvise – as opposed to simply moving from A to B – will therefore be key skills for leaders of the future. Navigating a route through the kind of complex change that AI will bring isn’t necessarily anything new for leaders. However, the scale and pace of the change that AI brings will be, and this means that weaknesses at the top are more likely to be exposed than ever before.

Challenge one: strategy – and structure

As decision makers, leaders will need not only to recognise and understand how their market context is changing but how to adapt and respond to that change. Only by doing so can leaders ensure their organisations stay ahead of (or at least keep up with) the curve, and remain relevant to those they serve. It is not surprising that boards are scurrying to ensure they include a top-notch chief technology officer, bringing digital understanding to strategic decision making – although technology executives are still poorly represented on public boards. 

A few companies have gone further. Back in 2014, a Hong Kong-based venture capital firm, Deep Knowledge Ventures, became one of the first companies in the world to appoint an algorithm, named VITAL, to its board of directors. VITAL supports fellow board members by providing information on potential investment decisions, scanning vast quantities of financial figures and other data on its potential future clients, as well as trends in the market. 

However, as the philosopher Voltaire was wise enough to suggest several centuries ago, it’s important to judge people ‘by their questions, not their answers’. Or, in the context of AI, the data currently produced is only as useful as the humans who feed in the data sets and analyse and interpret the results. 

Leaders must therefore ensure they not only have the right board make-up to respond to technology-led change, but that they have the right structures throughout their organisations, effectively surrounding AI with the human intelligence. This brings us to challenge two.

Challenge two: skills and motivation

In responding to change and staying ahead of the curve, a second absolutely critical element to success or failure for leaders will be whether or not they bring their workforce with them; both in terms of equipping their employees with the right skills to complement AI and motivating them to remain effective throughout a potentially long period of upheaval.

We are often warned about a lack of STEM skills that will needed to navigate the future. In a recent UK study by the Confederation of British Industry and Pearson, more than half of respondent companies were concerned that their future growth would be held back by
skills shortages. 

However, as AI-powered robots become easier for users to interact with, companies will need to focus on developing those skills that are distinctly human; for example, intuition, creativity, empathy, resilience and the ability to scan horizons and context in a way that adds value to the business. Getting this level, and mix, of skills right will be an important part of leaders’ future-proofing strategies, no doubt influenced by access to global talent, as well as home-grown training programmes.

 In terms of motivation, as with any disruption, change needs to be driven from the top with clarity, vision and consideration for those affected. And in doing so, leaders themselves will increasingly have to focus on their soft leadership skills, rather than proving their authority through knowledge and technical expertise. The latter skills may soon become augmented or replaced entirely by AI.

Fortunately, when it comes to helping both leaders and employees get to grips with rapid change, AI is not only the problem but part of the solution. For example, at my own organisation, Ososim, we have experienced the power of AI in helping to create training simulations that are so carefully modelled on the responses of the human brain, participants find them very persuasive and effective. These simulations are already being used by some of the largest companies around the world to help improve skills and capabilities in areas such as emotional intelligence, mental resilience and persuasion.

Challenge three: vision and purpose

old robot toy

Finally, while all this upheaval can sound deeply intimidating, we must remember that technology has been improving the capabilities we have as humans for decades. Until now, the focus has been more on what we are physically capable of doing. Technology has helped us to achieve things that our bodies were simply not capable of doing before – from flying thousands of miles through the air to communicating with one another across continents.

With the help of AI, technology is now enhancing our mental capabilities as well as our physical ones: crunching huge quantities of information in milliseconds, and using algorithms that flawlessly remember every correction ever made.

What technology cannot yet master is understand what it is actually doing and why; nor does it care. A robot kitted out with AI has no sense of ethics or purpose, equity or fairness, beyond what we humans tell it. 

And therein lies the third hugely significant challenge for today’s leaders and those of tomorrow: AI will be as ‘good’ or as ‘bad’ as humans make it. It was with this challenge in mind that, in 2014, AI research firm DeepMind insisted that if it were to sell its AI programme to Google, an ethics committee must be appointed to oversee its use.

It is imperative that human leaders, across public and private sectors, remain closely involved with the development of AI, challenging the data, putting it in context, and remembering that human creativity, vision and purpose may need to override whatever AI is or isn’t saying. AI may bring incredible progress, but it is our human leaders who must remain in charge of the moral compass.

Organisations such as the World Economic Forum have played a strong role in leading this kind of global discussion. They have set the challenge squarely at the door of leaders across the private, public and third sectors, in terms of how the fourth industrial revolution can be balanced with responsible governance and global goals, from the elimination of extreme poverty to gender equality. 

Business Schools, such as INSEAD, are putting the development of thoughtful, responsible leaders, at the heart of their missions. As the populist, negative emotions expressed by once-dominant groups, threatened by technological change, increasingly distract political leaders, so business leaders will need to provide the positive vision to guide inevitable technological advances.The human race has been through change before; our greatest strength as a species has been our ability to evolve and survive. But in each and every transition, leadership is key. Smart machines can make us smarter, and continue to drive our progress forward. But we must take nothing for granted. 

Strategy, motivation and vision will all be essential to how well we humans ride this next wave.

Jonathan Knight is CEO of global learning and technology company Ososim. He was part of the leadership team that established Accenture Learning and a founding member of the EU’s eLearning Industry Group. Jonathan has an MBA from INSEAD. His clients include BNP Paribas, Cisco, Deloitte, London Business School and the World Economic Forum.