“We are drowning in data and starving for wisdom.” This well-known quote gets to the heart of the strategic challenge we are facing, at a time when AI taking the world by storm. Perhaps even more pertinent, though, is the continuation of the original quote, which states that “the world henceforth will be run by synthesizers, people able to put together the right information at the right time, think critically about it, and make important choices wisely.”
Connecting the dots
We believe that synthesizers will be the winners of tomorrow. They are the ones who know how to make connections. Between people and technology. Between data sources. Between organisations. Between specialists in different fields. Between legislation and society. They are therefore also the parties who do not reason from technology itself but from understanding how technology can be relevant to business and/or society.
Synthesizers are capable of connecting the dots. For KPMG, this is the central idea with which we help organisations anticipate a new reality. This is essential, especially because history shows that the arrival of new technology is often accompanied by opportunistic responses to new opportunities (with or without use cases). However valuable that approach may be in the embryo phase, exploiting its long-term potential requires a more thorough rethinking.
So, what dots are involved in the increasing adoption of AI? We see the following perspectives.
Responsible use of technology
Trusted technology based on incisive choices
Machines are taking over tasks from humans – this fact is at the heart of the rise of AI – and this also means that decisions and actions, previously made and taken by a human, are being programmed into a machine. These include purely business decisions – such as pricing – but also ethical considerations, such as what is and is not morally acceptable. These decisions have traditionally been made by humans but are now increasingly being ‘hard’ programmed into systems. This can only be done responsibly if rigid standards (such as 'definition of success' and 'risk appetite') are defined extremely carefully. This requires, among other things, unerring insights the market and society, but also the ability to practically translate the choices made by the business to the developers of applications, so that they can develop 'trusted technology'.
Empowering employees
The work floor (partially) takes charge
IT has been democratizing for some time, with new AI tooling providing an unprecedented acceleration in this area, due in part to the great ease of use of a range of new applications. Employees can design their own work environment as they wish, without knowledge of programming languages (no-code/low-code). This not only leads to great creativity in optimising processes, but at the same time offers a solution to the shortages of programming skills in the labour market. The most fundamental consequence of this democratization is that it is the prelude to an organisational model in which decisions are made (much) more frequently on the shop floor.
Resilience in organisations
Responding to AI requires flexibility and empathy
There is no such thing as an ‘AI organisational culture’. That is too narrow a vision. There does exist an organisational culture that can deal well with turbulent and rapidly changing environments with ever-evolving issues. People still make the difference here. With AI taking over (parts of) people's thinking, the distinction in the market is made through other competencies. Think of curiosity about technological developments, empathy for (new) ethical issues, being able to guide people through uncertainty, and the ability to make sense of a world which is in a state of constant flux due to technology. These aspects can be summarised as resilience.
A combination of quick and thorough
Anticipating AI requires both quick wins and fundamental redesign
Every organisation can start working with use cases immediately with the currently available AI technology. These often deliver value from day one and have the nice by-product of stimulating the organisation to do more (from product-push to organisation-pull). Alongside this 'fast lane' that requires relatively little preparation, however, it is also necessary to go back to the drawing board to prepare the organisation for the more far-reaching consequences of the advance of AI. In a nutshell, executives need to pay attention not only to urgent but also important things. After all, the consequences of the rise of AI are particularly fundamental in the somewhat longer term, but it is precisely these long-term effects that are less immediately felt. However, proper preparation for this cannot wait until tomorrow, because this includes redesigning the operating model, IT architecture, data management, governance, capabilities, compliance and other issues. In terms of content, this preparation also involves leveraging as much as possible what we now know about (future) technology and experiences in other organisations.
A vision of ecosystems
Tomorrow's winners bet on collaboration in ecosystems
Using a single data source often has limited value in data analysis. It is precisely the combination of data sources that makes it possible to create value (by increasing efficiency/effectiveness). For example, think about how we can greatly improve the care pathways of individual patients through the seamless use of data from the different organisations involved around the patient, or how we can make container flows in seaports more efficient, and numerous other domains. Therefore, the true value of AI – which needs data as ‘food’ to show its value – will often only come into its own in concepts where the analysis of multiple data sources is possible. This is precisely why federated ecosystems – with some autonomy of participants but clear agreements on collaboration – are so important. Parties must now have a strategic vision of the place they want to fulfil in such an ecosystem.
