Robotization is very spectacular in its physical form, from simple toys for children to robots in factories or hospitals. But the current landscape of artificial intelligence has nothing to do with the Japanese automobile factory robots of the 80s. In reality, its development is already more impacting in its underground version, purely algorithmic and software. We went from manual tasks to intellectual processes. From the body to the brain. A breaking point was crossed in 2012, with the emergence of machine learning: it allows robots to improve themselves by developing a cognitive capacity. This revolution will have an impact on all professions: from lawyers to doctors to journalists, all of them must rethink the way they work and the services they offer their clients.
For the consulting industry, this revolution is twofold: it concerns its clients and their internal structure. Consultants already play a key role in the digital transformation of their clients. They are at the heart of the cognitive transition through the design and support of artificial intelligence programs. They must, therefore, design AI programs to serve their clients and, at the same time, support the deployment of the AI within their firm. In a word, change their own model.
First of all, because the consulting market is becoming more and more analytic-driven. Consultants need to identify and make sense of more numerous unstructured data sources. These are and will be increasingly available on the Internet or through social networks. The planned ramp-up of open data opens up almost unlimited fields with the evolution of regulations: these will always force more activities - public, semipublic or private - to make data available and to allow aggregation and to treat them. The consulting firms, with the correct organization, will be the best placed to profit from it.
Secondly, because the best consultants of tomorrow will be those who have the ability to select the most relevant potentialities for their clients. They will then be legitimate to support their customers in the industrialization of these approaches and their deployment. But more than mastering these technologies and their scientific dimensions, it is the relevance of the uses that will be decisive and the essential mission of the consultants will be to guide their clients by multiplying the proposals of use cases.
These approaches can be classified into four broad categories: Optimization, Augmentation, Prediction and Decision Support.
Optimization is the tip of the iceberg. It is based on the potential of automating a large number of tasks. It causes anxiety on employment because it is there that occur productivity grains, sometimes very high, far from conventional processes of continuous improvement.
Augmentation is the opposite. It allows enriching and innovates. It offers new products and services, which today are either unavailable or too expensive without the application of artificial intelligence. It is a fundamentally creative process that can create jobs. Insurers can now better guide their customers by accompanying them through smart cars and intelligent driver assistance systems or by protecting them from the risks of burglary.
Only yesterday, the prediction was a matter for science-fiction as in the Minority Report. However, these are now concrete cases, rooted in everyday behavior and events. Clients' exit risks can be better characterized individually. We can anticipate the intentions of moving at the disposal of retailers or of the cities’ planning and its forthcoming services. Credit card companies can predict divorces and key milestones in customers' lives by observing payment data. Electricity suppliers integrate the weather forecast into electricity generation or consumption. Cases of fraud could be anticipated and they would help a revolution in unemployment insurance. This is a multitude of use cases whose control can confer a major competitive advantage.
Lastly, the evolution of decision-making support enables action - both daily and in medium-term planning - based on correlation and scoring analyzes. It is no longer a tool reserved for management, it can be widely shared within companies. In a sophisticated - but already existing - version, artificial intelligence can predict emotions to improve customer service and enable it to better handle disgruntled customers.
The consulting industry must, therefore, operate its own cognitive revolution, without being afraid of a future which, I am sure, will prove infinitely more promising than some people fear. Similar to what is happening in industry 4.0, we need to develop a Consulting 4.0. Consulting companies that will stay away from this intelligence revolution will become mere transmitters. This can only be achieved under two conditions: investing in the development of AI programs and diversifying recruitment profiles by massively docking Data Scientists to existing teams. Several scenarios of AI penetration in the consulting business are possible: from simple support to substitution, through the most likely scenario, collaboration. With variants: from the development of industrialized platforms made available to client companies to the constitution of "use cases" proposed by expert consultants. The common approach consists of designing and deploying Consulting Bots that are intended to become real profit centers, sometimes small. Within three years, these activities could represent up to 10% of the consulting market.
One thing is certain: the consulting profession today is radically different from the one I knew when I created Sia Partners 18 years ago. Within 3 years, we will be more than 1,500 consultants, still growing and at the same time, we will have developed a hundred consulting bots. No consultant will work without digital tools based on artificial intelligence. We need to develop the "augmented consultant". The struggle between artificial intelligence and human intelligence will no longer exist but a new augmented intelligence will take lead.
Sourced from SIA partners.com