The speed with which change is taking place, and the magnitude of the impact, is huge. Everything we are doing is being driven by AI – it is changing the way we think and behave. AI is more than just hype, it’s here to stay.
According to our 2019 CEO Outlook Survey, only 20% of Belgian leaders and 13% of global leaders say that their organizations have implemented AI to automate some of their processes.
However, while business decisions are increasingly fueled by or made by algorithms, C-suite executives and the public question the trustworthiness of data and analytics. In fact, 56% of Belgian leaders and 68% of global leaders surveyed reported overlooking the insights provided by data analysis models because they were contrary to their own experience or intuition (2019 CEO Outlook Survey).
Beyond implementation, there is also still a lot of work for companies to do on the controls around these disruptive technologies.
While both in Belgium and globally just over half of respondents perceive their companies’ risk management systems as robust, in Belgium only 16 percent indicate it is able to capture disruptive risks (versus 21 percent globally).
8 trends in AI
- The time for experimentation is over. Companies are starting to move beyond the pilot phase and into implementation.
- Robotic Process Automation (RPA) is easier to implement, but the time for thinking that it’s the sole solution is over. Automation, AI, analytics and low-code platforms are converging.
- AI is currently being driven by supply – by the technology companies pushing it – but demand is growing.
- The organizational component is crucial. It’s not just about having the right talent but taking into account how you embed AI into your organization, looking at the funding model, questioning the return on investment, and ensuring accountability and reliability.
- Creating a Center of Excellence can help organizations keep up with the pace of change, but you still need the local / BU-level capability.
- Limited trust in the use and correctness of AI and algorithms raises concerns about the decisions made and actions taken. There is a clear need to develop a governance and control model for algorithms, to ensure the reliability, integrity and fairness of the outcomes and actions.
- You need an ecosystem – you cannot do it all by yourself. Find the right balance between having the capability in-house to understand what is being done with AI vs. developing it yourself. Then form the necessary alliances before your competition does.
- Every sector will be disrupted. There are already cross-sector use cases from predictive policing (Public Sector) to smart grids (Energy) to computer-aided diagnosis (Healthcare) to credit default prediction (Banking).
4 imperatives in developing AI
2 differentiators in the AI race
- Having trust
- Having the data – this is not only about in-house data, but can include external data that is combined into a unique data set
Questions boards/organizations should be asking
- How transparent should our model be?
- How fair should our AI be? Is it in line with our ethics and values?
- How accurate should it be? Are false positives OK for our business model?
- Is our organizational decision making based on valid analysis? How did we come to this result? (note: regulators and auditors will be asking this too)
- What’s the role of regulation on AI? Should we wait for it?
- Is our current set-up robust enough for future needs?
- Who is accountable for automated decisions and actions in our organization?
- Do I have the right controls in place?
The Board Leadership Center offers non-executive and executive board members and those working closely with them (including CROs and Heads of Internal Audit) a place within a community of board-level peers and access to topical seminars and ‘lunch and learn’ Board Academy sessions, invaluable resources and thought leadership, and lively and engaging networking opportunities.
Partner and Chairman, BLC Belgium
T: +32 2 7083686