An interview with the Head of Solution Delivery at Saratoga, Agnieszka Ceitil by Consultant, Inga Davids.
Artificial intelligence has gained traction across various industries and as a result it’s likely to disrupt and change many professions in the near future. McKinsey & Company estimates that as much as 45% of the tasks currently performed by people can be automated, and not only routine tasks, but also tasks which require knowledge capabilities.
The consultant role requires skills such as negotiation, creativity, leadership and strategic thinking which are all intrinsic human capabilities that cannot easily be simulated. So it must be asked, how will artificial intelligence impact the role and responsibilities of consultants?
Has AI become something organisations are actively using or will it still be a few years before organisations benefit from AI?
Although the concept of AI has become fashionable in recent years, with technologies like IBM Watson and home robots sparking the imagination of millions of people, the definition of what AI really is varies significantly. In truth, AI has already been in use in organisations for a long time. Anyone that has shopped on Amazon can attest to this – their engine for predicting your purchasing needs can very nearly read your mind.
Predictive AI such as in the Amazon example is machine learning based on analysing vast amounts of historic data and making predictions based on certain algorithms. It relies on patterns and repetition within data and requires vast amounts of computing power to process all this data. Now that processing power is abundant and easy to access, it makes sense that the adoption of AI across organisations will become more pervasive.
There is growing concern about artificial intelligence possible taking away jobs. Given this concern, to what extent do you believe AI will impact the role of the consultant?
We’ve all probably heard the newest buzz phrase, the ‘4th industrial revolution’. The idea is that the world is already in the throes of a fourth or digital revolution. This can be witnessed by the amount of disruptive technologies (think AirBnB, Uber etc) that have become common place in a very short space of time. As with any of the previous revolutions across history, job losses are inevitable. Uber has resulted in traditional taxi drivers losing their jobs. However, at the same time, new jobs and opportunities for entrepreneurship that have never before been conceived suddenly become common place. Uber has effectively allowed anyone with a reliable car to run their own taxi business.
Digitisation and AI, just like all complex technologies, have created massive opportunities in the consulting realm as organisations scramble to keep up and get value out of the latest technologies, but do not have the in-house skills to do so. In the short term, AI would create more demand for consultants that can help organisations implement practical AI solutions. Conversely, this very same technology will likely lead to a shrinkage of the consulting industry as AI becomes more advanced, however I believe this is a relatively long way off.
Machine learning and computers aren’t terribly good at creative thinking just yet. Do you think this will mean the ‘human’ element of consultants will be increasingly important in the world of AI?
The essential nature of AI is that it is based on learning from data and patterns. If you can see a pattern and apply an algorithm, you can automate it with AI. It stands to reason that any job that has repetition can be automated. Even traditionally high end professions such as doctors, lawyers and consultants have significant repetition that can be automated. This implies that although these professions will likely still exist the pool of ‘human’ lawyers and doctors and the demand for humans in these professions will likely significantly decrease in the next few decades, if not sooner. The same can be said for consultants.
However, any profession that requires creative, out-the-box thinking cannot theoretically be replaced by machine.
Let’s consider the Cynefin framework which categorises work into 4 separate domains: Simple, complicated, complex and chaotic.
A simple problem where the relationship between cause and effect is obvious, does not require much skill or education to solve, while a complicated problem where the relationship between cause and effect requires analysis may require more education and skills to address in order to analyse and solve the problem by applying expert knowledge. Historically, most work has fallen into the simple or complicated category. However technology and certainly AI will move work into the complex and chaotic category.
Complex is where the relationship between cause and effect is only apparent in retrospect. This is the domain that entrepreneurs find themselves in. It is not obvious what must be done as all learnt skills have been exhausted. You must now use your own creativity and wit to effectively ‘guess’ the solution and hope for the best.
Chaotic is where there is no relationship between cause and effect and where you cannot control the outcome. Here we do our best to survive and you cannot be given a formula or complete a degree to tell you how to handle this work category.
Whereas traditional consultants operate in the complicated category, with the progress of technologies like AI, consultants of the future will increasingly be expected to operate in the complex and chaotic categories.
The performance benefits and potential opportunities of automation are relatively clear, how will consultancy benefit from AI?
AI will provide many opportunities for consultants in the foreseeable future as companies try to navigate the complex world of machine learning and grapple with how these technologies can be relevant in their organisations. Consultants can help organisations determine where AI can be applied. As with any technological advancement, organisations will rely heavily on consultants that understand how these technologies can add value and even more so on consultants that know how to practically implement these technologies. Organisations will not have these skills in-house and many consulting companies are already setting up divisions that specifically focus on consulting in the AI space.
Moreover, in the long term, as the repetitive tasks that humans perform in their jobs are replaced by AI, there will be more opportunity and time for humans to focus on the more creative aspects of their professions. This will apply to the consulting profession as much as it will apply to other professions. I believe this would lead to more job satisfaction and provide us the ability to focus on the things that are important rather than being weighed down by all the menial tasks that have to be done.
Since you have an intimate view of talent and hiring. How will consultants need to future-fit their careers?
Traditionally a consultant’s job was to apply learned standards and benchmarks based on experience in order to solve a problem. Companies like Accenture developed standards, methodologies and benchmarks that their consultants learnt and then applied to their various clients. This is essentially a repetitive task and can therefore theoretically be replaced by AI (eventually). The distinction in the future will not be a consultant that can apply a benchmark or a standard, but the consultant who can truly think out of the box and apply creative solutions specific to the business in which they are consulting. Consultants of the future need to be open minded, insightful and creative.
To quote Andre Bourque a freelance journalist specialising in high growth industries: “..Consultants need to offer value that exceeds what technology will soon be able to do by itself. Gone will be the need for the traditional consultant, who delivers a report that is a restatement of the obvious — and stamps that presentation with the ‘prestige’ of the logo of his employer”.
This is nothing new, since the 1980’s, the only segment of ‘jobs’ that have shown significant growth were ‘non-routine cognitive jobs’ in other words, jobs that create systems rather than jobs that use systems.