Holistic AI adoption: the key to unlocking enterprise value

Date:
Fri, 12 Jun 2026 08:51:37 +0000

Description:
While AI adoption is accelerating, 77% or organizations still report no meaningful impact on overall revenue.

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 The benefits of AI tools are well understood, with almost 20% of UK businesses already deploying the technology. Yet while adoption is accelerating, 77% still report no
meaningful impact on overall revenue.

This points to a growing gap between adoption and return on investment, one driven in part by organizations treating AI as a standalone technology initiative rather than a business-wide transformation. Philip Miller Social Links Navigation

AI Strategist, Progress Software. Closing this gap requires a more holistic approach, embedding AI across the organisation and aligning it to core business objectives. Latest Videos From Watch full video here:

That means identifying where AI can deliver measurable value across
workflows, while establishing clear guardrails so deployment is secure, responsible and scalable. Defining AI with purpose Before adopting AI, organizations must clearly define what they want to achieve. Without specific objectives, even the most advanced tools risk under-delivering. This starts with identifying priority outcomes, such as revenue growth, operational efficiency or improved decision-making, and aligning AI initiatives directly to these goals to drive measurable impact over time. You may like Everyones doing AI, but whos seeing value? Why AIs investment must materialize for the C-Suite Why a staggering 42% of business AI projects are currently failing

It also requires determining where AI should and should not be applied. While AI works best when embedded across the organization, not every process benefits from automation . Misaligned use cases can introduce unnecessary complexity without delivering value.

By mapping business challenges to AI capabilities, organizations can focus investment on initiatives that support strategic priorities and deliver tangible results. 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
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Taking this approach helps ensure AI adoption remains purposeful as it
scales, evolving from experimentation into a core business capability. In turn, this creates a strong foundation for broader, more effective enterprise-wide deployment. Making AI work in the flow of business Once objectives are clearly defined, the next step is embedding AI into existing workflows. The most effective implementations dont disrupt how teams operate but enhance it, reducing time spent on manual tasks, streamlining reporting and enabling more informed, data-driven decision-making.

This also means meeting employees where they are. AI adoption cannot rely solely on users stepping outside familiar workflows or rapidly upskilling in entirely new tools before they can realize value. Instead, organizations should focus on bringing AI capabilities into the systems, processes and interfaces employees already use with confidence. What to read next
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When AI feels like a natural extension of existing work rather than an additional layer of complexity, adoption becomes easier, trust grows faster and the path to measurable business impact becomes clearer.

Technologies such as retrieval-augmented generation (RAG) play a key role in this process. By connecting AI systems to trusted internal and external data sources, organizations can help ensure outputs are accurate, relevant and grounded in real business context.

This not only improves the quality of insights but also builds confidence in AI, enabling employees to make decisions based on reliable, context-rich information rather than assumptions or incomplete data.

Ultimately, the highest-value AI use cases are not always the most complex, but those that integrate naturally into day-to-day work. Organizations seeing the greatest impact are redesigning workflows to operate in partnership with AI, adopting a human-centric approach that balances automation with
oversight.

Leading institutions such as HSBC and NatWest Group are already embedding AI across operational, customer and risk management processes to drive
meaningful outcomes. Governing AI at scale Adopting AI at scale requires establishing the guardrails that allow it to operate safely, effectively and in alignment with business objectives. This begins with defining clear policies for how AI is used, where it delivers value and where human
oversight remains essential, giving employees the confidence to use AI responsibly.

Regulatory compliance is also central to this process. While the UK does not yet have a single, unified AI regulation, organizations must ensure their use of AI aligns with existing legal and regulatory frameworks, including data protection and privacy requirements. Taking a proactive approach to
governance helps reduce risk while enabling innovation.

Ongoing monitoring is equally critical. AI systems must be continuously evaluated to maintain accurate, unbiased outputs aligned with business goals. By tracking performance and refining models over time, organizations can
build trust in AI while helping it continue to deliver measurable value.

Ultimately, closing the gap between AI adoption and business impact requires
a holistic approach. Rather than deploying AI in isolation, organizations
must align it to strategic objectives, embed it within workflows and govern
it effectively, laying the foundation for sustainable, long-term returns. We list the best free data recovery 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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