The AI gap nobody's talking about
Date:
Thu, 26 Mar 2026 15:21:58 +0000
Description:
Despite AIs rapid advancements, training resources on secure and efficient AI use are still limited.
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 Tech Radar Pro 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
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Despite AIs rapid advancements, training resources on proper, secure, and efficient AI use are still extremely limited. As an example, while prompt engineering plays a crucial role in enabling modern AI users, theres still a lack of education around this critical skill. Article continues below You may like The key to the UK's AI success lies in closing the skills gap Closing AI learning gaps between leaders and employees AI fatigue is real and its time for leaders to close the organizational gap Joel Carusone Social Links Navigation
SVP of Data and AI at NinjaOne. Without a strong understanding of the fundamentals, and with a blind reliance on AI capabilities alone, users may churn out workslop or outputs that function but lack judgment, nuance, and quality. Ultimately, it is putting their organization, customers , or even their own credibility in jeopardy.
In order to fully reap the benefits of AI in 2026, users must get better at discerning where and how to properly apply it pairing thoughtful use of the technology with regular education and enablement to achieve optimal outcomes that dont compromise reputation or security . Beating common AI myths Across the organizations Ive worked with, there are two AI myths that continue to show up.
The first: Use AI everywhere. Find ways to implement it widely, invest in it deeply, and let the returns speak for themselves. 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.
AI is like a slow burn it takes targeted investment and curation to keep progress alight. If you let it burn too brightly, it could destroy entire operations. Were not yet at a place where we can fully trust autonomous AI with our most sensitive business materials and decision making.
The best use cases always keep a human in the loop, who can spot when AI doesnt quite get it right. In IT, where uptime and security are mission-critical, we rely on experienced professionals to make judgment
calls.
With the right training, they can safely automate repetitive tasks and free
up more time for the kind of edge cases that absolutely require human intervention. What to read next How AI will collide with data readiness AI projects worldwide are failing in businesses because of this simple reason
Its time to walk the walk with AI
Myth two: AI is one size fits all. AI is far from a singular use case. Its application is incredibly broad and varied. For organizations to make the
most of AI, start with clear objectives and small use cases. From there,
train teams, add guardrails and validation processes, and collect feedback. Then iterate.
AI isnt just a solution, its a skill. It requires hands-on practice, reinforcement, and a willingness to adapt in order to drive maximum wins. The organizations that build genuine adoption will treat AI skills like any other craft. Theyll create a space to experiment, learn from others, and improve through real work. The coming split LinkedIn data shows AI literacy has
surged by 177% since 2023. But even with people using AI everywhere,
education and understanding havent kept pace.
Over the next five years, we will see a clearer divide emerge in how business leaders approach AI education and enablement. One group will treat AI skills like Microsoft Office in the 90s, keeping it as a checkbox exercise that everyone must do.
The other group will develop real capability, from contextual prompt engineering to output validation frameworks and responsible-use protocols
that match their goals. This divide wont just show up in efficiency metrics.
It will show up in quality, trust, customer experience , and the performance of entire teams. It will be evident in more advanced AI use cases, and expedited decision-making.
Major organizations are already embracing this shift and racing to stay ahead of the enablement curve. Walmart is launching AI upskilling programs with OpenAI. Accenture has publicly confirmed that it may exit any employees who cannot be upskilled.
AI education has evolved from an optional initiative into core workforce planning. What this moment really means AI literacy is the bare minimum. Organizations that place value on prompt engineering, critical thinking about outputs, and intelligent collaboration with AI tools will attract both top talent and partners in the future.
Acting on the current momentum requires a flexible and pragmatic approach, as organizations will need to pair thoughtful adoption with regular education. The next generation will not treat AI as something new or intimidating.
They will treat it like Wi-Fi: expected, invisible and essential. They will walk into the workforce ready. The real question is whether the workforce
they enter will be ready for them.
This is the time to close the gap, not because AI is exciting, but because
the organizations that thrive will be the ones that find creative ways to use AI to augment existing human capabilities boosting productivity,
streamlining processes, and allowing people to grow in their roles (thus growing business as a result).
The AI gap that no ones talking about (or people arent talking about enough) remains enablement and at the end of that day, thats not due to faulty technology, that comes down to a lack of investment in people.
The organizations that act now, investing in both AI and enablement to fuel progress, will set the standard everyone else will eventually follow. We've featured the best AI website builder. This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and
brightest minds in the technology industry today. The views expressed here
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