Looking at two questions & answers from Gartner's conclusions flags some red alerts in my mind.

 1) 'How do I set an AI strategy, get started with use cases, and determine and realise measurable business value'?

▶️ 92% of CIOs believe AI will be implemented in their organizations by 2025 (more than any other technology).
▶️ 61% of organizations have assigned AI teams and accountability to the CIO.
▶️ 21% of CEOs say AI is the top disruptive technology;  #FOMO a fear of missing out may drive behaviours.

‘AI will be implemented@ is such a vague answer. Given that AI grew in use from the mid-20th Century and ranges from simoplke algorithms to extractive AI, through machine learning to this year’s raging topics GenerativeAI and AgenticAI 92% seems a low figure. What have the other 8% iof CIOs been doing?

Then the FOMO factor is illuminating. 

Salesforces CIO recently said:  

'CIOs are under increasing pressure to generate business value from generative AI, but Salesforce CIO Juan Perez is among those IT leaders who believe such impatience from the C-suite could doom many projects.

“The explosion of AI has really put CIOs in the spotlight and placed the CIOs in the hot seat like never before,” says Perez, fresh off two industry events in which many of his CIO colleagues say they feel they are between a rock and a hard place. “It is really clear to me how CIOs and other tech executives from all kinds of organizations are being challenged as to how they can to move quicker, but also responsibly, with AI.”

The enterprise landscape is littered with Version 1.0 generative AI proof of concept projects that did not materialize into business value and have been dumped. While the industry remains in the early stages of uncovering and implementing AI use cases into business workflows, the blueprint for success remains elusive for many CIOs.'

It is challenging enough deploying machine learning and RPA without the distractions of GenerativeAI and the high pressure from CEOs fuelled by vendor incentives to trial LLMs and products like ChatGPT, ClaudeAI, LLAMA  and so on. 

There is no short-cut to proper strategic planning to pin value on potential use cases. Chris Surdak and I have managed a global transformation project and he kindly summarised the key tasks to avoid the risks of FOMO.

1. Executive adoption decisions based on something other than FOMO
2. Compelling use cases 
3. Honest and complete business case ROI
4. Systems engineering thinking
5. Effective test campaigns
6. User buy-in
7. Understanding of the technology's true capabilities
8. Understanding of the technology's true limitations
9. A back-up plan
10. Self-reflection over prior failures

In the post ‘Pilot  Purgatory’ phase this approach is vital if insurers are to pin realisable value on optimal use cases. That approach will also help counter the answers to the second Gartner question and answers below.

CIO Question 'How do I demonstrate business value from technology investments'?
▶️ 81% of boards have not made progress toward or achieved their digital business transformation goals.
▶️ 70% of digital leaders have not significantly advanced toward digital transformation goals
▶️ 67% of #CFOs believe digital spending has not met enterprise expectations for the last three years.
 

There are many reasons for these replies by CIOs- not least the chains binding them to legacy and mixes of more modern yet inflexible core systems that are policy-focused rather than customer-centric.  

Modern MACH-architected core systems are the key to escaping those chains and whilst current CoreTech will not be changed overnight by most insurers a step-by-step approach can suffice. 

For now, insurers can bridge the yawning gaps at the intersections of data from legacy technologies, point application software, core systems of record, and the data silos of largely unstructured data.  

Data automation engines are key to this. That is the first stage to achieving the data maturity vital to leverage the varied box of AI tools and technologies . You can find much more about this in the articles below.

GenAI passed Gartner's peak of expectations- CompositeAI is the key to value
‘By the end of 2024 ( and during 2025), value will be largely derived from projects based on familiar AI techniques, either stand-alone or in combination with GenAI, that have standardized processes to aid implementation. Rather than focusing... Read more 
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C-suite expectations may be too hasty (and underinformed) to deliver meaningful AI value in a responsible manner.
'CIOs are under increasing pressure to generate business value from generative AI, but Salesforce CIO Juan Perez is among those IT leaders who believe such impatience from the C-suite could doom many projects . “The explosion of AI has really put... Read more
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Prioritising outcome goals leveraging AI- productivity/cost-cutting, increasing revenue, transformative competitive advantage, or all of these?
I should emphasise that Generative AI is one of many tools that insurers can leverage to help achieve corporate goals. GenAI will not ensure an insurer will set the right vision, goals, and strategies, or allocate the optimal resources to be... Read more
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Forces Horizon avoids AI generating a ‘sea of sameness’ in job applications
Large Language Models (LLMs) have now trained on such large data sets that they've run out of data. One of the reasons OpenAI, Claude and other vendors now create synthetic data. By definition this creates a dumbed-down version of the data... Read more 
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Insurers Can Parlay Technology into a Competitive Edge- but too many don't!
"Making deft use of data—from information collected by flood sensors at a manufacturing plant to a driver’s photographs of a crumpled car panel—has become a prime source of competitive advantage for insurance carriers. Zettabytes of data, much of... Read more
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How technology in claims processing is changing consumer choices in insurance
“According to a recent survey by Insurity, a pioneer in cloud-based insurance software and analytics, a noteworthy 52% of consumers expressed a preference for insurers who invest in new technologies to enhance the claims experience following... Read more 
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Surveys highlight data maturity holding back AI deployment ambitions
Three recent surveys with excellent representative samples research different aspects of business and all come up with the alarming confession by insurers that their ambitions to leverage enterprise and third-party data to drive transformation and... Read more 
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All in all, paths to help avoid the barriers to transformation CIOs discussed with Gartner.