Digital transformAItion, 2026-style

Business operations are going to evolve in the next 12 months as AI takes hold, say industry observers, turning digital transformation into transformAItion. 

The greatest barrier to AI transformation isn't the technology, it's leadership hesitancy and slow decision-making at the top," said Megan Hughes, MD, JAPAC, HubSpot.

"HubSpot research has found that as businesses become more digitally mature, roadblocks shift from infrastructure limitations to internal bottlenecks. Close to four in 10 (39%) fully-digitalised businesses in Singapore cite slow decision-making as their biggest growth barrier, with one-third (33%) experiencing leadership hesitancy around adopting new technologies like AI at scale."

Hughes shared: "I've seen this firsthand across the region. Business leaders are excited about AI's potential, but many remain stuck in pilot mode, running small experiments without the conviction to embed AI across core operations. The proof is in the data: companies with leadership championing AI adoption are seeing dramatically different results than those taking a wait-and-see approach.

"When leadership hesitates, even the best AI strategy stalls. True digital transformation requires C-suite champions who can make rapid, data-informed decisions and create a culture of experimentation. In 2026, we expect more companies across JAPAC will move toward empowering leaders with formal AI frameworks and usage guidelines, shifting from cautious observation to confident execution. The window for 'wait and see' is closing. As AI becomes embedded in how businesses operate, the gap between leaders and laggards will widen dramatically."

Ajay Patel, GM, Apptio and IT Automation, IBM, also sees the C-suite taking responsibility for technology and finance performance in 2026. "Shared accountability for business performance, cloud and technology spend will lead to even greater collaboration among CFOs and CIOs, reverberating across organisations.

"Speed of change and rising cost of AI and cloud will require breaking down the functional silos. Technology business management (TBM) will become the connective tissue that enables these key leaders to work together cohesively, not just to manage budgets, but jointly optimise value," he elaborated.

"Beyond the senior-most level, we’ll also see people within organisations take on greater accountability for business and financial performance driven by technology – from the CIO role all the way to individual engineers." 

Source: Dataiku.
Douetteau.

Florian Douetteau, Co-founder and CEO at Dataiku, touched on shifting roles and responsibilities as well. "In 2026, AI will sit at the centre of business operations, forcing companies to confront a long-ignored question: who actually owns AI transformation? 

"The answer won’t be the CEO or COO alone, but a new hybrid executive role that blends operational rigour with the Chief People Officer’s mandate to drive adoption, trust, and upskilling. Without this combined leadership, companies will end up with either ungoverned chaos or perfectly governed systems that no one actually uses," he predicted.

AI will increasingly underpin business operations in 2026, bringing with it new challenges.

Source: Syniti. David.

Cody David, Head of AI & Innovation, Syniti, part of Capgemini, said that companies will expect intelligent operations across finance, supply chain, and HR operations as a baseline capability. 

"Automation will expand, but only where the data is reliable, harmonised, and governed. To scale automation with confidence, organisations will demand traceability. That means lineage, provenance, and decision logs so teams can answer what happened, why it happened, and which data drove the outcome," he said. 

"It also means clear ownership and stewardship so the business knows who is accountable for the inputs." 

"Modernising ERP landscapes, establishing clean core architectures, and aligning processes across systems provides a sound foundation. But without business ready data behind it, intelligent operations will create faster work and faster errors at the same time. In 2026, trust becomes the KPI."

"In this AI-centric era, the challenge for businesses would be to move beyond just bolting AI onto legacy systems and instead embedding it into every step of their operations. This means redesigning workflows end-to-end, rethinking processes, upgrading tools and reshaping how teams work so the entire system is AI-ready. The early phase of digital transformation – that simply puts existing tasks online – is on its way out," said Sima Saadat, Singapore Country Manager, General Assembly.

"While these approaches were useful a decade ago, they can’t keep up with the speed and complexity companies face today. What’s incoming and here to stay are 'AI-native' practices, where AI is built directly into how software, data and design teams operate."

The challenge for businesses will also be to train every knowledge worker to become 'AI-native', rather than relying on a small group of specialists," Saadat added.

"That’s why at General Assembly we’ve also redesigned our Software Engineering, Data Analytics, and UX Design bootcamps to embed tools like ChatGPT, Copilot and Figma AI into day-to-day practice and not as an afterthought."

FinOps

Financial intelligence will become easier to access, Patel said. "The AI era requires faster, smarter and financially-grounded decisions. Organisations across multiple sectors will require near real-time, integrated financial and operational information to make sound business decisions," he forecast.

"The need for true systems of financial intelligence that eliminate data silos, connect cloud costs to business value, and democratise financial insight for every user. Instead of juggling disconnected, complicated dashboards, teams will begin to expect unified insights that tie spending to performance, efficiency and outcomes, driven by artificial intelligence."

FinOps is poised to become a core business capability, he added. "As AI capabilities develop further, FinOps will simultaneously go under a noticeable evolution next year: one that shifts the practice from a manual, report-driven specialty into an automated, AI-powered capability that delivers real-time intelligence directly to engineers, product teams and business leaders," Patel said.

"AI will surface optimisation opportunities, forecast cost impacts, and embed financial context into everyday decisions. With this forecast in mind, FinOps will transform from a specialised practice into a core business capability and evolve from a 'back-of-house' function into a foundational discipline that empowers teams to become stewards of smarter, data-informed decisions."

At the market level, the consolidation of the FinOps market is going to pick up speed, leading to a significant shakeout as organisations move away from individual tools and look for more consolidated, all-in-one platforms, Patel said.

"With more than 80 vendors offering point solutions today, the space is just too crowded. By 2026, customers will want fewer platforms that handle everything—cost management, forecasting, automation, optimisation and engineering workflows—in one place.

"And this shift will increasingly sit under a broader technology business management (TBM) framework, with ITFM and FinOps becoming the two main pillars for managing the financial side of all tech investments. Just like smartphones absorbed a bunch of standalone devices, and the AI market is already narrowing into a few major platforms, when things get too noisy, customers naturally lean toward simpler, consolidated options—FinOps included," Patel said. ITFM stands for IT finance management.

At the product level, Kai Wombacher, Product Manager, IBM Kubecost, sees AI-powered innovation in FinOps. "AI will accelerate innovation in FinOps tools; for example, making dashboards easier to use with natural language interfaces for querying data and digging into usage anomalies,” he said.

ITOps

Mark Ablett, VP, Asia Pacific and Japan at HPE Networking, said that with conversational AI copilots and agentic assistants becoming embedded members of the IT team, "the traditional workflows of dashboard-hopping, manual triage, and endless ticket queues will fade". 

"Generative AI accuracy and functionality have reached a tipping point, and AI will manage the first line of support: answering routine questions, resolving policy conflicts, identifying anomalies, and even auto-initiating RMAs," Ablett said. An RMA is an authorisation for the return of merchandise. 

"The next generation of experts won’t just configure networks but will partner with AI copilots to manage thousands of endpoints with the precision of one. Engineers won’t spend their time navigating dashboards; AI will surface insights, take action, and guide decisions through natural language interactions. 

"The most effective professionals will be those who not only know how to configure but also know how to teach and collaborate with AI: shaping prompts, validating intent, and orchestrating automation at scale. In 2026, the network engineer becomes a strategist, and AI becomes the operational backbone."

The Japan and Asia-Pacific region is sometimes referred to as JAPAC.

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