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With over 20 years of experience within IT, Cannon Lafferty knows the value of keeping up with the latest in technological advances. While at the beginning of his career that meant an upgrade to Windows XP, in his position as Head of Consulting at Adaptavist it means keeping ahead of AI.
But AI is no Windows XP. Cannon believes the mistake companies are making now is viewing AI as an additional feature, an upgrade, rather than a transformational force. No wonder he predicts that “we’re going to see organisations embrace AI as an integral part of their infrastructure”.
This rise in AI’s prevalence, however, will come at a cost. Bad actors are already benefiting and that will only increase as models advance. That’s why Cannon points to the need for a greater investment in “defensive AI systems that can adapt and respond to these threats” in real-time.
But Cannon’s vision isn’t all gloom. He believes advancements in IT will help close the gaps in social inequality by simultaneously “making complex subjects accessible across different education levels” and “growing accessibility to increasingly sophisticated technologies”. Let’s hope so.
With Cannon’s vision for the far future made clear, we wanted to know what he expects in the short term. That’s why we started by asking him about the most significant changes he expects to see in the near future.
We’re going to see organisations embrace AI as an integral part of their infrastructure, rather than treating it as an additional feature within their application stack. But this shift requires viewing AI as a core platform capability that increasingly automates both trivial and complex administrative tasks. In many cases, configuration and decision-making will move away from manual processes or code, and instead be driven by natural language interaction and AI summarisation.
To support this evolution, organisations will need to embed data modelling and model operations into their core competencies. As human intervention is reduced across these systems, demand will grow for new frameworks and regulations around testing and quality assurance, particularly to ensure trust, reliability, and accountability in AI-driven environments.
As organisations and their IT teams continue to move towards SaaS-based ecosystems, the way IT professionals view data will need to evolve. Data is going to need to become the principal asset, and organisations must actively govern it with strong controls in place to ensure its integrity, security, and strategic value. This means data will have to sit at the heart of how organisations approach IT, with a greater emphasis on controls, consent, cataloguing, and archiving.
AI will benefit everyone, and this unfortunately includes malicious actors. Zero Trust, or “never trust, always verify,” will need to become the baseline approach for organisations, which means getting buy-in from the whole C-suite, not just CISOs. As AI-powered attacks become more sophisticated, security architects will need to design systems that can withstand attacks that learn and adapt in real-time. This means investing in defensive AI systems that can adapt and respond to these threats.
We’re going to require a stronger focus on identity and context-based access controls, data microsegmentation, and continuous authentication, all of which will become fundamental for IT teams addressing cybersecurity challenges.
IT will enable these industries to innovate at a much faster pace by creating unprecedented levels of interconnectivity between organisations and facilities across the world. In healthcare, for example, breakthroughs in telemedicine and robotics are already enabling remote surgeries and consultations.
Research is another area where industries like this can expect to see real transformation. Researchers from anywhere in the world will be able to conduct research using datasets that were previously inaccessible, as well as gain access to a larger number of them. The number of doors this opens is endless.
IT enablement will help close gaps in social inequality by making complex subjects accessible across different education levels, while growing accessibility to increasingly sophisticated technologies will reduce the need for commuter-based work.
As far as social inequality is concerned, IT could provide broader access to healthcare and education through digital platforms, especially when telecoms infrastructure reaches those located in the most rural geographies. Meanwhile, digital identity solutions are emerging as a powerful tool for financial inclusion, enabling underserved populations to access banking services, secure loans, and participate in the digital economy.
Cloud computing will drive rapid growth in data processing disciplines such as modelling operations, cataloguing, lineage, and access. Over the last couple of years, large organisations have been relying on single-provider setups. This has all changed after the recent spate of large-scale cyber attacks; companies are now diversifying to reduce risk, improve resilience, avoid vendor lock-in, and therefore optimise costs. As a result, data security and access will become core competencies that organisations will need to establish and govern.
The future of cloud computing will likely see more sophisticated hybrid architectures that optimise workload placement based on multiple factors, including energy efficiency, data sovereignty, and processing requirements. This evolution will require new tools and frameworks for managing complex, environmentally conscious cloud deployments.
