- September 7, 2022
- Posted by: Bernard Mallia
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A Structural Break in What We Are Used To in managing projects
Cognitive technologies require a different way of thinking and of managing projects. We are not just talking about new tools and technologies, even though these also have an important role to play. We are dealing with a new paradigm that changes the way we think, behave, interact and formulate strategy. The traditional waterfall model of project management is not fit for developing and deploying cognitive technologies.
They require the adoption of a more agile approach that, while being compliant with a growing set of heavy-handed regulations, is better suited to the constantly-changing landscape of AI and ML. This means being able to rapidly prototype ideas, test them in the real world and iterate on them based on observed performance and feedback.
It also requires a shift in mindset from thinking about projects as linear journeys with a defined beginning, mid-point and end. Instead, we need to think about them as ongoing experiments that are constantly evolving and to manage them as programmes with no defined end-date rather than projects.
This is by no means an easy transition to make, but it is essential if we want to be able to harness the power of cognitive technologies. They need to be melded and fused with business objectives from the very outset and not treated as a technology project in silo.
AI is also a new way of doing things and it requires organisations to learn, experiment and change their processes, and this is usually one of the factors that gives rise to resistance from employees who are used to the status quo and find its certainties comfortable. AI investments also need to be made with a long-term view in mind. Many of the benefits of AI will only be realised over time as employees get used to working with the technologies and as the data sets used by AI applications grow larger and more representative.
It is also important to remember that AI is not a silver bullet – it will not magically fix all of an organisation’s productivity and management problems. But if used correctly, it can be a powerful tool for improving productivity continuously and for ameliorating management efficacy.
Organisations need to be prepared to invest significant time and resources to reap the benefits of AI and can’t hope to be able to reap the AI dividend if they are running their business as a cash cow which they are prepared to milk to death without ever reinvesting in it. They also need to have a clear understanding of what they want to achieve with AI and how it can help them meet their business objectives over time. Only then will they be able to develop the necessary infrastructure, processes and culture required for success.