Continuing from the Organisational Leader and Artificial Intelligence Part One, which looked at the What and Why of AI, Part Two addresses the When and How. The context of my writing is still Uganda – which I know extends to many countries in our beautiful and resource-rich continent.
When AI?
We are lagging far behind as a country, and even those businesses or government agencies that have some use cases are not at the forefront. The time to harness AI is yesterday, not tomorrow. The national government, the business sector, educational institutions, the researchers – we all have a role to play because creating the required technology environment, the skills, the policy and regulatory environment demand collective approaches to be at the top of our national agenda. We need the collective approaches, all stakeholders on board, to ensure sustainable progress.
How AI?
One of the areas in which we provide expert support to organisations as Knowledge Consulting Ltd is dissipating the mists earlier mentioned so that the Boards and C-Suites get a better understanding of the what, why, when, and how to get to the next level of performance through exploiting AI – while at the same time appreciating and addressing the risks and pitfalls. I need to note in this context that AI, like any other technology, is not stand-alone: synergy is created through a full integration of the technologies of the fourth industrial revolution as appropriate for the organisation as part of their Digital Agendas. These could include information systems that exploit blockchain, the internet of things, high-speed connectivity, robotics, and
high-density energy sources.
A common source of failure in many organisations is that they leave the what and how of technology introduction to the engineers: I have personally lived through more than two decades of leading organisational, national, regional, and continental transformations, transformations that required getting top-level leaders to appreciate and accept the fact that introduction or enhancing of any technology suite within the organisation is a strategic decision that is the responsibility of top management and the Board.
Your mechanic knows how to repair your vehicle better than you can; and your driver is better at getting you to your destination more efficiently than you can; but only you can decide on what kind of functionalities you want in that vehicle, or to which destination the vehicle should be driven. One of the causes of slow digitalisation, and now adoption of AI in Uganda if that we entrust the decisions and direction as well as the investment to the mechanics and drivers. Each of you colleagues decided which kind of phone you wanted, and you largely know how to use it – but only a small minority knows how the phone works.
When you make the when, why and how to introduce technology in your organisation an engineering decision, you will end up with costly investments that do not lead to increased productivity or a better bottom line. A golden rule in digitalisation: “Align technology to organisational goals, not organisational goals to technology”. It is where you want to go, and at what speed, which determines the means of transport you choose.
With specific reference to generative AI tools, a strong general caution relates to being aware that since large language models that sit at the core of such tools that in turn rely largely on what is available on the internet, the biases one finds on the net become part of the driving logic behind decisions or guidance provided. What is worse is that AI can hallucinate, really a polite technical term for making up things (just like we do) which are
then delivered in very convincing language to guide decisions. It is therefore important to always remember that AI is still a tool, and not a replacement for human judgement. Another risk is that over-reliance on AI that can then compromise human ability to think through matters and make rational context-based decisions.
Finally, as part of the “How” we need to be cognisant of the reality that exploiting AI is not just about the technology – it is also about the need for both up-skilling and hiring the necessary skill sets to ensure that the outcomes are beneficial to the company.
What about the Board? To elevate their oversight and strategic guidance roles, we need to turn our Boardrooms into situation rooms where company performance is visualised in real time. Many of our organisations, the biggest being our government, have not seized the opportunity of data, although it has been said for a long time that data is the new gold (We prefer to call it the new gold ore at KCL).
We now have the tools to easily mine the data and extract the pure gold using AI. If we can master this, we can shift our organisational outlook from looking backwards to set future direction, to predicting the future using current data, and best of all to apply prescriptive analytics: deciding the course of action that will lead to the results we want to achieve. We no longer need to wait for the outcomes to know whether we took the right decision: we can see the outcome in current time and refine planned action to optimise it. The Boardroom becomes a situation room.
In summary, the role of organisation leadership starts with gaining sufficient understanding of the non-technical aspect of AI to ensure strategic alignment with organisational or business goals; selecting the best approaches to integration; identifying and managing risks; proper curating of organisational data as a premium resource; and change management. All this needs to be done in an environment that considers regulatory requirements (especially personal data privacy) and ethical considerations.