Let's start with a true story about the Battle of Waterloo, which was fought on Sunday 18 June 1815.

Facing each other were the French emperor Napoleon Bonaparte, who for more than a decade had dominated European and global affairs, and Arthur Wellesley, the Duke of Wellington, who had made his military name during the Peninsula Campaign of the Napoleonic Wars, and ultimately rose to become one of Britain's leading statesmen and politicians.

Waterloo is located about 15 kilometres south of Brussels. On that day, the French army comprised about 69,000 men and faced an opposing force of about 67,000 troops, although this number was to swell to over 100,000 with the arrival of Prussian allies before the end of the day. By nightfall, Wellington emerged as the victor, but nearly 50,000 from both sides were dead or wounded. According to Wellington, this was ‘the nearest-run thing you ever saw in your life'.

There are many explanations for his success. One that resonates is that that there is evidence that he was in the area during the summer of 1814, having taken a wide diversion from his route from London to Paris where he was taking up his new role as British ambassador to the court of Louis XVIII. Rather than taking the more direct route from Dover to Calais, he sailed on HMS Griffon to the Belgian port of Bergen Op Zoom, accompanied by ‘Slender Billy', the 23-year-old Prince William.

He spent two weeks touring the Lowlands, and the valley south of Brussels seemingly caught his attention. There's a suggestion that he stayed at the inn La Belle Alliance, a location that was to play a part in the eventual battle.

At that time there was no hint on the horizon that he would ever fight his old adversary Napoleon, and perhaps his visit was simply the old habit of a retired soldier. During the battle he was so aware of the terrain that he was able to deploy his troops to the greatest effect. During the fighting he took care to allocate particular regiments to protect key defence points, such as Hougoumont. Without these insights, some argue that Wellington's success would have been uncertain.

Two hundred years later, perhaps there is a still lesson to be learned from this encounter.

Whilst we shouldn't think of the introduction of AI to business as being a battle, there are definitely significant challenges ahead. How well we humans prepare and respond to that environment will depend significantly on how prepared we are. Like Wellington, understanding the terrain may not be enough in itself, but it will provide a useful indicator about what might happen and what we should do about it.

This book can't provide all the answers, or even all the questions. Perhaps, at best, all it will give us is some sort of compass in a sea of data and analytics that will provide guidance as to how the world of work will evolve. But in uncertain oceans, isn't a compass still useful?

It seems that almost every time we pick up a newspaper or read an online article, there is some reference to AI. It's difficult not to reflect on how it may – or may not – change the way we live and how we will work in the future. As we read the articles, we can become either excited or confused (or perhaps both) about what AI really means, why it's happening, and what will be the consequence.

The articles tend to be either quirky or technical. On the one hand, they suggest how AI can help choose the best and quickest route, keep the elderly from feeling alone, and assist with the best retail choice. On the other hand, technical articles also imply that beneath the covers are numerous algorithms of a complexity that normally gifted humans cannot possibly understand – and that this topic is best left to expert academics and mathematicians with deep statistical insights.

These experts seem at face value to be the people whom we will have to trust to create some sort of compass or road map for all our futures, yet how much do they understand your world or your work?

AI is a topic that is much more important than a means of simply providing a clever satellite navigation scheme or some form of novelty tool for aiding personal decisions. It is a concept that potentially goes right to the core of how we will work and even how we will exist in the future. As individuals, we should not only feel that we have the right to know more about what this matter is actually concerning, but that we should become contributors to the discussion. Through greater understanding we become more empowered to enter into the debate about the future, rather than leaving it to others. But beyond simple empowerment, don't we also have a duty to become part of the discussion about our future – that is, your future?

This isn't the first book about AI and certainly won't be the last. But readers who don't have deep technical, academic qualifications or experience in computer science or advanced mathematics increasingly need to understand what is actually going on, how it will affect them going forward, how best to prepare, and what they can do about it.

It's important to be realistic about the time frame involved. It wouldn't be to anyone's benefit to worry unduly today about a technology that won't be in full implementation for another quarter or half a century, but many suspect it will happen much sooner than that. In many places there is evidence of it already beginning to happen. Industries, professions, and individuals need to be prepared, or to start to become prepared.

A recent paper, ‘Further Progress in Artificial Intelligence: A Survey of Expert Opinion', interviewed 550 experts on the likely timescale for development of AI.

In the paper, 11% of the group of eminent scientists surveyed said that we will understand the architecture of the brain sufficiently to create machine simulation of human thought within 10 years. And of these, 5% suggested that machines will also be able to simulate learning and every other aspect of human learning within 10 years. They also predict the probability of the machine having the same level of understanding and capability as a Nobel Prize-winning researcher by 2045.

Of that group, even the most conservative thinkers indicated that they believe there is a ‘one-in-two’ chance that high level AI ‘will be developed around 2040–2050, rising to a nine-in-ten chance by 2075’.¹ Who can really be sure?

It's impossible to make predictions about timing with certainty. Some people might have doubts about implementation timelines proposed by academic experts. On the other hand, businesses that operate in demanding and cutthroat climates are continually looking for competitive advantage, which invariably comes from appropriate technological advances. The drive for competitive advantage, most probably through cost cutting, will force the development timetable. To do so effectively requires business practitioners to better understand technology, and for technologists to have a greater grasp on business pains and opportunities.

As market conditions increasingly accelerate the pace of change, there is a real possibility – or more like a probability – that some professions within certain industries will be using some forms of AI within the next 10 years; that is, by the mid-2020s. Whilst many organisations remain obliged to manage their progress in terms of a series of short-term goals, in strategic terms this date is just around the proverbial corner, and they need to start working towards it now.

Even if the more conservative, longer-term view (that we will not see AI until 2040) is taken, the shift to AI will almost certainly occur within the lifespan of the careers of graduates and interns joining industry today. In their book The Future of the Professions, lawyers Richard and Daniel Susskind make the case that professionals (especially those between the ages of 25 and 40) need to have a better understanding of the potential paradigm shift from the influence of technology on the way they work, suggesting that ‘professions will be damaged incrementally’.²

This is not an issue that will only affect individuals working at that time. Those still working today, who will have finished their full- or part-time employment within a decade, will find their daily personal affairs being increasingly influenced by AI in terms of services provided to them.

The issue therefore may not be what and when, but rather how. The problem may not be of crystallising what we mean by AI, or conceptualising what we can do with it, but rather how it can be effectively and sensibly deployed.

Some of these same issues have already occurred due to the adoption of advanced analytics (i.e. predictive and prescriptive analytics), so we will attempt to consider the question of implementation from a practical point of view. Although the implementation time frame of one decade or even three is not absolute, this book makes the brave assumption that AI in the form of advanced analytics will eventually be with us in one form or another. Regardless of the period of time involved, the book proposes that there are a series of incremental building blocks and an optimum implementation route that should be followed. If organisations are to take advantage of AI within a single decade, then the journey to change needs to start immediately.

Some industries are more likely to be affected by AI than others: those that involve much repetitive decision-making, have extensive back-office functions, or are not specifically customer facing are particularly suited to AI implementation. They will respond and implement at different speeds but changes as a result of AI will lead to an environment of knowledge sharing. It is entirely feasible that we will see the sharing and cloning of complementary technologies used in quite diverse markets, such as consumer goods, retail, financial services, medicine, and manufacturing. Effective transfer of technologies and capabilities from one industry to another may ultimately become one of the most critical types of innovation going forward.

Manufacturing will increasingly and rapidly embrace robotics driven by superadvanced, or cognitive, analytics. But to what degree should specialist professions, such as dentists, surgeons, publishers or even many parts of the creative-arts sector, feel threatened?

There will also be immense cultural issues for the workforce to cope with. To what degree will our traditional understanding of the meaning of work change? The book will consider who will suffer (or benefit) the most. Will it be the blue-collar workers, whose role will become partly or fully automated? Will it be knowledge workers, who find that their most valuable personal commodity – knowledge – has become devalued and replaced by super search engines operating in natural language? Alternatively, will it be the business leader, whose authority, based on experience and judgement, will be undermined by systems offering viewpoints on the probability of success of any given decision?

In any event, how will business leaders even be able to lead unless they have personal experience? The very nature of leadership will need to change, and we will look at that as well. What can any – or all – of these groups do to prepare themselves?

Location may also be a key driver for change. In some growing markets, such as Asia and Latin America, new AI technologies could become the first resort for providing services where there has been a massive existing or potential market unsupported by adequate professional talent. The consequence of this could be that relatively immature marketplaces could start to leapfrog established practices to satisfy market need. What might be the implications of creating a new global world order, in terms of the use of machine learning?

We will also think about the impact of change through AI on existing business models. Traditionally, the way of doing work has been relatively linear in nature: one thing happens, and then another thing happens. Will the use of AI herald a change to that modus operandi, and if so, then how? What also will be the impact on traditional views of operational risk (risks of failure of systems, processes, people, or from external events) – especially if the decisions are being made by computers in an automated way?

One of the key enablers for change rests with professional institutions in whose domain is vested the awarding of professional qualifications. Many of these institutions are already struggling with the concept of big data and analytics as they try to convince their members that these trends are more than a fad or hype. In the near future an even greater burden will fall on their shoulders to carry the flag for AI and for new ways of working.

The choice whether to do this or not is not negotiable, insofar as on the whole the younger members of these institutions will increasingly adopt what are described as liquid skills, which reflect a new way of learning, to broaden their personal capabilities. Increasingly, many younger professionals see the ultimate goal of personal development and upskilling as being that of the ability to go solo in the world of work and to earn a crust through value creation rather that a regular paycheck. To what degree will this affect professional institutions and how will AI help – or hinder – this aspiration?

This book is not about the deepest technical details of technology and mathematics – although we will touch on these to give context and raise awareness – but rather aims to help individuals understand the impact on their business environment and their careers. As far as practically possible, it will help practitioners start to ‘future proof’ their careers against changes that are already beginning to happen, might occur in under a decade, and almost certainly will occur afterwards.

AI is not a subject without potential controversy. Not only are there technical and professional issues to contend with, but there are also some ethical aspects to consider as well. At a broader level, readers will gain a level of insight that allows them to contribute to the wider discussion in a more informed way.

Beyond this, the book aims to help employers supported by professional institutions start to ensure that their employees and their leaders have the right skills to cope with a world of work that is transforming rapidly and radically.

Overall the focus is on raising awareness in individuals, professional organisations, and employers about a future world of work that will be with us sooner or later. My guess is sooner – and that there is no time to lose.