AI is working, but only for the individual

Date:
Wed, 22 Apr 2026 10:25:31 +0000

Description:
Many implementations of AI continue to fall short when it comes to improving team collaboration.

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! Become a Member in Seconds Unlock instant access to exclusive member features. 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. You are
now subscribed Your newsletter sign-up was successful Join the club Get full access to premium articles, exclusive features and a growing list of member rewards. Explore An account already exists for this email address, please log in. Subscribe to our newsletter Despite widespread enthusiasm for AI tools among employees and organizations, many implementations continue to fall
short when it comes to improving team collaboration.

Companies have typically only focused on the outcomes they want to achieve, without giving equal attention to how those outcomes will be delivered in practice. Part of the challenge is that AI is still widely viewed as a tool for boosting individual productivity . While this does create value, it overlooks a far greater opportunity to transform how teams work together. Article continues below You may like From curiosity to culture: Advocating
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Product Innovation Lead, Miro. As a result, a gap is emerging between AI investment and meaningful business impact. In one study, only 15% of AI decision makers reported a revenue lift for their organization over twelve months, suggesting that AIs potential is still not translating into results.

To realize the full potential of AI, organizations need to change their mindset. Instead of thinking of individual outputs, leaders must now think about how to turn AI adoption, experimentation and success into a team game. Its the rollout, not the tech thats holding back ROI In recent months, a wave of high-profile job-cuts attributed to AI have signaled a fundamental shift
in how organizations are structured.

Yet in the rush to adopt the technology, many have prioritized access to the tech over a robust strategy, with employees vocalizing their concerns over a lack of clear guidance on how they should be used or how they are trained.
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.

As a result, employees are left to navigate AI on their own, while leaders continue to cite gaps in technical skills and workforce readiness as the primary barriers to implementation.

Without clear direction usage becomes inconsistent and siloed, limiting opportunities to scale impact across teams. More concerning, however, is this lack of oversight increases the risk of inaccurate outputs or the mishandling of sensitive data which can expose organizations to operational and reputational risk. Building for teams The next challenge lies in how effectively organizations enable teams to work together, something that still feels out of reach for many businesses. While nine out of 10 decision makers view collaboration tools as critical to AI success, 75% say tools remain focused on individual productivity. What to read next Closing AI learning
gaps between leaders and employees Stop chasing the AI silver bullet Why so many businesses are still on the wrong side of the AI divide

Organizations need to move beyond isolated use cases such as meeting
summaries or copy generation and instead integrate AI into shared workflows, bringing it into the environments teams already use together, rather than relying on standalone tools.

This shift reduces the friction of switching between platforms and helps standardize how AI is applied across teams. It leads to more consistent outputs and stronger alignment around shared ways of working.

Progress also accelerates when teams experiment together rather than in siloes, sharing insights and adapting in real time. Organizations need an
open dialogue to see what really is and isnt working. Transparency is
critical to turn these learnings into a meaningful advantage, particularly in a period defined by ongoing change and uncertainty. The path forward,
together Strong leadership is another important factor when it comes to driving impact with AI. Measurable business transformation depends on leaders embedding AI into day-to-day operations and clearly articulating where it
fits within the broader strategy.

When a senior team leads by example and demonstrates how they use AI themselves, it signals that adoption is a core part of how the organization
is evolving and how to get the most out of the technology.

We have also found that as AI gradually becomes more embedded in workflows, knowledge that once sat with individuals becomes accessible across the team. This opens up new opportunities for shared learning, supported by communities of practice where teams exchange insights and tackle challenges together.

Many organizations are reinforcing this through initiatives such as internal AI days or hackathons, where teams showcase experiments and working prototypes. These efforts not only highlight practical use cases but help to normalize AI as a collaborative tool, with cultural shifts that compound over time to drive meaningful, organization-wide impact.

They also allow people to get hands on and help teams simultaneously upskill the knowledge, engaging in a collaborative way whilst solving problems with AI. Success will not come from isolated experimentation AI has already proven its potential to reshape how work gets done, but real impact will depend on how organizations choose to implement it. The gap between investment and results is not a reflection of the technology itself, but of how it is introduced, embedded and scaled across teams.

Closing this gap requires a shift in mindset. Success will not come from isolated experimentation or individual productivity gains alone, but from enabling teams to work differently together. This means putting the right structures in place, embedding AI into shared workflows and fostering a culture where learning is collective and continuous.

Organizations that take this approach will be better positioned to move
beyond incremental improvements and unlock meaningful, organization-wide transformation. We've ranked the best employee management software . 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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