Why the next technology conversation shouldn't start with AI

Date:
Thu, 27 Aug 2026 10:28:10 +0000

Description:
AI adoption succeeds when cloud, security, data, and governance work together.

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 Artificial intelligence may dominate today's headlines, but the most productive conversations I'm having across the technology ecosystem rarely begin or end with AI.

More often than not, they start with a business challenge. Francisco Criado Social Links Navigation

SVP of Cloud, Security & AI at TD SYNNEX. Business challenges are driving the AI conversation How do we modernize our infrastructure without increasing complexity? How do we strengthen our security posture while enabling innovation? How do we prepare our organization for AI without rebuilding everything from the ground up? Latest Videos From TechRadar Watch full video here:

Those questions quickly lead to a realization: today's technology decisions are interconnected.

An AI initiative depends on cloud readiness. Cloud strategy influences cybersecurity. Identity, governance and data management underpin all of it.
On paper, they look like separate line items. In practice, they're one
system. If you pull on cloud, security moves with it; if you pull on AI, data and governance move too. You may like Why AI success starts with teams, not tech The next AI phase is better agents not bigger models The biggest barrier to AI success isn't AI

That's a significant shift, not only for organizations investing in technology, but for the partners helping them navigate it. Organizations are moving beyond asking whether AI matters. They're focused on how to implement it successfully.

That shift is happening across the industry. 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
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Our fourth annual Direction of Technology Report, which surveyed more than 1,400 IT solution providers across 40 countries, found that nearly 75% of partners say AI is essential to their future. Yet the same research shows the conversation has become much broader than AI itself. Partners increasingly
see services, specialization, cybersecurity and automation as the
capabilities that will differentiate them in the years ahead.

To me, that's one of the most important signals in today's market, because
the conversation isn't simply about adopting the next technology. It's about building an environment where technologies work together to solve real business challenges. From experimentation to implementation AI adoption is accelerating, but organizations quickly realize that successful AI
initiatives depend on much more than selecting the right model or platform. They depend on secure infrastructure, trusted data , governance, integration and the expertise to bring those pieces together. What to read next Why tech vendors are key to solving AI's adoption problem The AI Scaling gap: why ambition is outpacing readiness Why connecting tech to operational reality will help businesses deliver on AI's promise

The market data tells a similar story.

Global AI spending is projected to exceed $2 trillion in 2026. Global Public Cloud spending is expected to surpass $1 trillion, while cybersecurity spending is projected to continue its rapid growth. These markets aren't growing in isolation but expanding together because organizations recognize that one investment reinforces the others.

That's why I believe the conversation is maturing.

The question is no longer, "Where do we start with AI?"

It's, "How do we build the right foundation to make AI successful?"

That requires a different approach from everyone in the technology ecosystem.

Customers aren't asking for another AI demonstration, but theyre asking questions like: How does AI fit into the technology investments we've already made? How will it integrate with our existing cloud environment? What does it mean for our security posture and governance? How can it improve productivity without creating unnecessary complexity? Those are implementation questions, and I believe they'll define the next phase of AI adoption.

Technology will keep evolving, and AI will evolve fastest of all. What gives me confidence is not the pace of that innovation but the way the industry is organizing itself around the harder work of implementation.

No single vendor, provider or advisor holds every answer. Environments have become too interconnected for that, and the organizations making genuine progress are the ones drawing on combined expertise, weighing infrastructure, security, data and services together rather than in sequence.

The definition of success is changing with it. What matters is no longer how many technologies an organization can reach, but how well those technologies operate as one system in service of a business outcome. That, far more than any single breakthrough, will determine who ultimately gets value from AI tools. We've featured the best AI website builder. 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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