AI has exposed the biggest knowledge gap in business. Hint: it isn't technical

Date:
Thu, 27 Aug 2026 10:58:14 +0000

Description:
Companies have spent the last two years racing to adopt AI, but new evidence suggests many have overlooked the one thing that will determine whether those investments succeed: their people.

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter Of the expected $2.5 trillion that corporates are due to spend on AI this year, over $1 trillion is set to be allocated to IT services and dedicated software . That is a huge chunk of change for a technology that many are still grappling with and trying to understand how it fits with their business, team, and procedures.

A few years since the ChatGPT-enabled revolution started, were beginning to see the different approaches and challenges businesses are facing when implementing AI. David James Social Links Navigation

L&D expert and Chief Learning Officer at 360Learning. Ford's recent decision to bring back experienced engineers after AI systems failed to catch manufacturing issues offers an important lesson for every business investing in AI. At the same time, new research from Ramp and Revelio Labs, covering almost 22,000 US companies, found that organizations investing most heavily
in AI are actually hiring more people, not fewer. Latest Videos From
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Together, these stories tell us something important. Everyone assumed AI
would reduce reliance on people, but instead were seeing companies discover how dependent AI is on experienced people. AI may be changing how work gets done, but this alone isn't enough for growth and success. AI is accelerating work, but experience still matters Earlier this year, Ford re-hired 350 veteran engineers after AI and automated systems failed to deliver quality work, demonstrating that employees are critical to a successful AI rollout. You may like AI value is stalling but the issue isnt the technology Why AI success starts with teams, not tech The gap between AI potential and AI reality Is a leadership problem

Its also interesting to see this reflected in Ramp and Revelio Labs research that organizations investing in AI are hiring more people. Instead of neglecting hiring and skills development, companies increasingly need the right team members to help refine and improve sophisticated AI so that it performs better in the areas they need.

Success with AI still depends on understanding the skills people need to perform, at an individual, team and organizational level, then investing in development that reflects the realities of their work. But before organizations can build those skills, they need to know where expertise already exists. Too many businesses are sitting on critical knowledge without any clear view of who has it or where the gaps are. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.

One way to achieve this is building a skills ontology, a living record of the skills that exist across the organization.

Rather than relying on assumptions, businesses can identify where they overindex or underindex on capabilities, understand which teams have specialist knowledge and spot gaps before they become business problems. It also creates the foundation for workforce planning, internal mobility and
more effective AI deployment. The most valuable skills inside your organization Now you have an effective skills ontology, you have an overview of what is going on in your organization. This helps you identify the subject matter experts (SMEs) that exist across a business, but whose knowledge has often never been formally captured - such as that mythical AI power user.
Take Ford, which has said it is using its rehired employees specifically to train younger staff and reprogram AI tools . What to read next Stop measuring AI usage. Start building AI capability. Rethinking data science skills in the AI era: Practice still matters From apprehension to AI agency: the leadership shift no one can outsource

Once youve identified where expertise exists, AI can help maintain that picture and keep it up to date as roles evolve. But understanding where the expertise exists is only the beginning.

Organizations need to validate that expertise, connecting people to targeted development opportunities and making it easier for SMEs to share what they know with others. Importantly, this learning should be embedded in work as much as possible rather than separated from it, so it improves performance where it matters most.

AI makes knowledge easier to organize and distribute, but it doesnt create
the judgement that comes from experience. It can surface patterns and recommend learning pathways, but it cant explain why a process works, when to challenge it, or how to adapt it to the realities of your organization.

Thats why experienced team members remain essential. They contribute the context that enables AI, and everyone else, to use that knowledge
effectively. Turn expertise into a competitive advantage At a time when many in areas like HR and Learning and Development (L&D) felt that AI would diminish their role, it's clear that this expertise is only becoming more valuable.

L&D teams have the opportunity to operate more strategically by owning the upskilling and reskilling agenda, turning their and team members expertise across the business into a competitive advantage, and putting the processes
in place to create agile workforces that collaborate effectively with AI.

AI has put organizational expertise firmly in the spotlight, whilst also highlighting that too many businesses are sitting on a wealth of knowledge that exists only in the heads of experienced employees. Not only do they know and understand more about a business and its processes, but they can also provide judgement - a scarce resource that AI cannot replicate.

Getting this information out and deploying it across the business will create a workforce that becomes smarter every time someone learns, rather than
losing knowledge when someone leaves, leading to fewer repeated mistakes, better quality and stronger internal mobility.

To get the greatest return from their employees and from AI, the top organizations need to ensure they are investing in identifying, sharing and scaling the expertise they already have instead of simply buying more software. We've featured the best online learning platform. This article was produced as part of TechRadar Pro Perspectives , our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit



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