businessinfomag.uk magazine 28 don’t have IT teams with technical experience in AI and there is virtually zero understanding of what/how to monitor it from a cybersecurity perspective. Corey Keyser Head of AI, Ataccama Agentic AI expands the data workforce instead of shrinking it For years, people have predicted that AI will hollow out data teams, yet the closer you get to real deployments, the harder that story is to believe. Once agents take over the repetitive work of querying, cleaning, documenting and validating data, the cost of generating an insight will begin falling towards zero. And when the cost of something useful drops, demand rises. We’ve seen this pattern with steam engines, banking, spreadsheets and cloud compute. Data will follow the same curve. As agents make it painless to ask and answer questions, entirely new parts of the business will begin participating. Units that once earned upstream. The result is not just faster queries, but a new rhythm of decision-making where insight becomes conversational, not transactional. Mike Puglia Kaseya Labs General Manager Massive AI push ends in major data breaches Every single company is under enormous pressure to deploy AI. It’s the wild-west as companies bring the technology in-house to replace processes, customerinteraction etc. in perhaps the largest deployment of an untested/ poorly understood technology in IT history. Organisations simply Jay Limburn Chief Product Officer, Ataccama Natural language becomes the front door to data For over a decade, business users have asked when they’ll be able to just ask a question and get a real answer from their data. In 2026, that question finally becomes routine. Text-to-SQL moves from proof-of-concept to production, not because of flashy frontends, but because the foundations underneath – semantics, lineage and quality – are strong enough to support it. This shift doesn’t remove analysts from the equation; it amplifies them. Analysts spend less time translating vague requests and more time interrogating the business itself. Meanwhile, users across marketing, operations and finance gain direct access to governed answers, not guesswork. It works because the stack is now ready. Definitions are consistent, pipelines are observable and trust has been Last year was all about AI and this year will be no different. With the technology changing so fast, what developments can we expect over the next 12 months and what will the implications be for the deployment and use of AI in business? We ask the experts for their 2026 AI predictions. Ask the experts AI PREDICTIONS Deepak Singh Chief Innovation Officer, Adeptia First-mile data becomes AI’s new power source Enterprises will realise that AI’s real leverage point isn’t the model but the first-mile data flowing into it: the messy, inconsistent information arriving from customers, partners, brokers and legacy systems. As this scattered data becomes the biggest obstacle to automation and AI accuracy, organisations will shift attention upstream. The priority will be normalising and enriching incoming data before it hits AI workflows. Companies that get that right will see faster operations, more dependable AI outputs and a dramatically smoother path to true AI-driven transformation. Enterprises hit pause on legacy migrations Enterprises will rethink costly ‘lift-and-shift’ migrations and instead focus on modernising legacy systems through smarter integration layers. As AI-native tools collide with non‑native, decades-old systems and processes, the industry will realise that modernisation doesn’t require ripping anything out. By wrapping legacy platforms with APIs and AI-ready connectors, organisations can expose hard-to-reach data, preserve proven business logic and experiment with AI and automation faster, bridging the gap between legacy reliability and next-generation intelligence. Industry-specific AI and vertical SaaS will outpace horizontal platforms Enterprises will accelerate their shift away from broad, horizontal SaaS tools towards verticalised platforms and AI models built for the nuances of their industry. These specialised systems will deliver smarter automation, faster performance and lower compute costs by focusing on tightly defined data patterns and workflows, far outperforming one-size-fits-all solutions. As proprietary data and domainspecific intelligence become competitive differentiators, companies will favour platforms that understand their business out-of-the-box rather than forcing customisation on generic tools.
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