Over the past two years, artificial intelligence has dominated boardroom discussions and investment plans. Many companies have tested AI in limited ways, but in 2026, the focus is shifting from experimentation to execution.
Cutting Through the Hype
Concerns about an “AI bubble” continue, fueled by high valuations. Bruce Martin, CEO of Tax Systems, says the real challenge will be separating hype from genuine value.
He adds that a potential bubble “popping” could be positive. Companies would gain clarity on which AI applications truly help and which are distractions.
Martin believes disciplined adoption will outperform chasing the latest tools. Companies that simplify processes and equip teams properly will emerge stronger.
Pragmatic Growth Across Industries
Terry Storrar, Managing Director at Leaseweb UK, notes that AI is moving from explosive hype to practical growth. Businesses will focus on initiatives that improve efficiency and customer engagement rather than speculative projects.
Susan Odle, CEO of StorMagic, says organisations are pacing investments carefully. Flexible systems and strategic planning will help companies withstand financial pressures.
Buyers Demand Evidence
Expectations around AI are hardening. Jay Hack, VP at Fluke Corporation, warns that curiosity is no longer enough. Buyers now demand proof of results, not just potential.
Companies must show tangible outcomes to stand out in 2026.
Scaling Intelligence in Supply Chains
AI is moving beyond pilots, especially in manufacturing and supply chains. Simon Bowes at Blue Yonder highlights that resilience now means systems that learn, adapt, and anticipate challenges.
74% of industry leaders report AI is already transforming operations. The next step is scaling deployment, unifying data, and empowering teams to act on AI-driven insights.
AI in Retail and Customer Experience
Nicola Kinsella of Fluent Commerce says agentic AI will help companies respond in real time to disruptions like weather events or port delays. Teams can act automatically, minimising customer impact while fulfilling promises efficiently.
Data Storage Remains Critical
Carlos Sandoval Castro at IBM highlights the rise of unstructured data from generative AI. Traditional storage cannot keep up. Companies will need hybrid solutions that combine cloud with cost-effective long-term storage like tape, providing both scalability and savings.
Cybersecurity in the AI Era
AI increases the demand for integrated security. Martin Gittins of Commvault stresses that resilience now requires combining security, identity, and recovery into a single framework.
Mark Skelton at Node4 warns that AI-driven systems will attract cyberattacks. Businesses must implement strong governance and safeguards before widespread deployment.
Laurie Mercer from HackerOne predicts that by the end of 2026, most enterprise security teams will use AI-based tools for triage, detection, and response.
Humans and AI: New Skills Needed
As AI becomes integral, new skills will be essential. Charis Thomas of Aqilla calls this “prompt literacy,” the ability to interact effectively with AI tools.
Chris Lloyd at Syspro emphasizes that AI relies on quality data. Leaders who trust AI as a partner will help their teams move faster and evolve smarter.
The Next Chapter of AI
In 2026, AI will no longer be about hype or quick rollouts. Its success will depend on credibility, clear outcomes, and thoughtful implementation. Companies that focus on these factors will gain a real competitive advantage.
