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Q&A with Sarah Burnett, VP Research, Everest Group
Sarah Burnett, Vice President of Research at Everest Group in London, focuses her research on digitalization and automation. Here Burnett – chair of “BCS [British Computer Society]) Women” and one of Computer Weekly’s “50 most influential women in U.K. IT” – shares her views on the impact of artificial intelligence on organizations.
What is the likely effect of artificial intelligence on how work is done in organizations?
The use of AI will change the way that we work. That is for sure. One of the biggest challenges all organizations will face is how to manage people and skills over the next five to ten years. I mean everything from the total number of employees to recruitment levels, from developing skills and creating new roles to succession planning. Thanks to automation, the number of people needed to deliver lower-skilled transactional work is going to decrease, leading to a smaller base at the bottom of the traditional organizational pyramid. Add AI to the mix, and the number of people needed to deliver some knowledge-intensive work will decrease, shrinking the middle layer of the pyramid. The decline in the number of junior-level positions means organizations will have to rethink their hiring processes. But they also will need to figure out how to grow and develop staff to fill senior levels in the future.
Another impact on work is the “watching and learning” nature of AI. Some of the learning done by AI involves watching what employees do and in the process it is probably able to assess and identify potential performance problems. HR departments and business leaders will have to work out how to deal with this.
How can organizations make the transition to automation and AI while maintaining their ongoing processes?
AI means a move towards what we call “codified consciousness” in IT infrastructure services automation. Organizations have to adapt to this changing world and develop new skills and capabilities. Automation software applications are designed to integrate with most systems. The usual route is to start small, trial automation by doing a proof of concept, then scale up using the lessons learnt from the PoC. When it comes to smart automation, there is a period of learning for the AI before it can actually start to work. During that period, it will be watching and learning and can be deployed gradually, by activating it in test environments, then testing and validating its actions before moving into live processes.
What sort of AI investments should organizations be making?
Organizations need a coherent and business context centered IT infrastructure service automation strategy. A disjointed strategy will inhibit enterprises from realizing the benefits of IT infrastructure investments. For example, you might have a strategy for adopting some kind of X-as-a-Service model, but without a coherent strategy you end up with little automation and find it hard to efficiently manage its operations.
I also recommend taking a 360-degree approach to investments. Investing in technology is one thing but, with AI, it is also very important for organizations to invest in training for general awareness about AI at all levels of organization. I do not mean just the people who would deploy AI but all who will be impacted by it.
Where should organizations start in trying to leverage the benefits of AI?
There are certain use cases that have become synonymous with uses of AI in an IT setting—for example, AI handling L1 and L2 problem resolution and reducing resource requirements and costs. But the typical use cases only scratch the surface of AI’s potential. Just as AI engines need to learn about us, we need to learn about them and what they can do for us. That requires a new organizational mindset. At present, most businesses typically try to shoe-horn technology into existing operational and business models – doing things in the old way but with new technology. As we learn more about AI, we need to keep an open mind and be ready to accept how we can do things in entirely new ways.