Evolutionary Intelligence – How the Constrained CIO achieves business value from AI

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Here’s how a CIO can address various constraints to increase efficiency, reduce cost and deliver value across a number of different areas in the enterprise.

In my recent LinkedIn blog, The Constrained CIO – Addressing increasing demands for change against a background of constraints, I discussed how my customer, the Constrained CIO, was challenged by an increasing demand for change in a real world constrained by legacy applications, infrastructure, methods and models. It is a situation I see every day and in the blog I describe ways to address constraints to increase efficiency, reduce cost and deliver value across a number of different areas.

Capgemini’s recent analysis, Turning AI into concrete value: the successful implementers’ toolkit, describes one of those areas of change, Artificial Intelligence (AI), and provides compelling evidence that AI is now generating tangible benefits as it moves out of hype mode. The significant majority, greater than 75%, of organizations that implement AI are seeing over a 10% increase in sales, operational efficiency, and customer satisfaction in addition to the ability to make decisions based on improved analysis.

The analysis provided is global, across sector, very thorough, and, as I said, compelling but the “issue” that this causes is an increased demand for change. Clearly in the big picture this is really a great opportunity with tangible benefit that is aligned to business strategy, but in order to manage the IT service delivered to the business, our CIO must balance the delivery of value with the need to maintain stability of existing assets.

The report distills the analysis obtained to provide insight as to how to balance the opportunity with the challenge. The recommendation is to adopt a pragmatic, evolutionary approach that supports the advice in my previous blog—to make sure that incremental value is achieved, the direction is assessed on a regular basis to ensure flexibility, and to continuously check that the direction is aligned to business strategy. In this sense, I believe the “use case” section of the report will be particularly helpful to give guidance around how to identify quick wins as well as the more longer-term opportunities.

But a word of caution before we get too excited by new technologies and change, don’t forget the existing stuff! As with any new, edge technology, the risk is that additional complexity is added which becomes essential very quickly. It then becomes just another legacy system to maintain and cost to incur. Any considerations around integrations strategy, asset ownership or rental, use of resulting big data, etc. should be at front of mind to ensure we are seeking to reduce our constraint burden as we increase our value. I’ll further expand on some of these ideas when I look at some other recent Capgemini insight relating to the company—Bluestock, that is achieving new ways to optimize its own operations through reducing constraints.

In summary, in the equations of Application Economics, AI is a large-value credit that is now maturing to deliver benefit that businesses have been waiting for. To ensure that we don’t incur a large constraint debit, we need to think about how we manage both the existing applications that will be integrated to as well as in the new technologies coming on board. Ultimately, a new paradigm of Applications Management thinking is required to help the Constrained CIO to deliver profitably as the speed of technological change increases.

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