An SAP study shows that Singapore organizations are now spending an average of US$14.5 million (S$18.9m) a year on AI — but 91-percent say their data and governance foundations “need a complete overhaul” before they can scale further. With AI adoption accelerating faster than visibility, integration and risk controls, below are predictions by Apptio’s spokespersons about how AI adoption will possibly pan out.
Eugene Khvostov, Chief Product Officer, Apptio:
Unlocking ROI through product-based operating models
“By operating cross-functional teams like product development engines – where there are defined sprints, pre- and post-mortems, with clear OKRs and more scrutiny on how the business is performing – organizations will unlock more agile ways of working. Powered by AI and automation tools, teams will be more in tune with what’s working, what’s falling short, market and customer needs, in order to bridge the gap between strategy setting, execution and outcomes.”
Kai Wombacher, Product Manager, IBM Kubecost:
AI cost optimization and aligning spend to business value
“In many cases, companies have been so focused on the AI horse race that model cost considerations have been deprioritized. As organizations face increasing pressure to demonstrate AI value and align investments with business outcomes, FinOps for AI will gain traction as a critical framework to understand and optimize AI and infrastructure spend. At the same time, 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.”
Ajay Patel, General Manager, Apptio and IT Automation, IBM
- Real-Time Financial Intelligence Across Industries
Prediction 1: AI era requires faster, smarter and financially grounded decisions. Organizations across multiple sectors will require near real-time, integrated financial and operational information to make sound business decisions. The need for true systems of financial intelligence that eliminate data silos, connect cloud costs to business value, and democratize 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.
- The Evolution of FinOps into a Core Business Capability
Prediction 2: As AI capabilities develop further, FinOps will simultaneously go under a noticeable evolution: one that shifts the practice from dashboards and report-driven specialty into an automated, AI-powered capability that delivers real-time intelligence directly to engineers, product teams and business leaders. AI will provide predictive insights, surface optimization opportunities, take well-grounded actions, forecast cost impacts, and embed financial context into everyday decisions. With this forecast in mind,FinOps will transform from a specialized practice focus 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.
- Shared Accountability for Tech and Finance Performance
Prediction 3: Shared accountability for business performance, cloud and technology spend will lead to even greater collaboration among CFOs and CIOs, reverberating across organizations. 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 optimize value. Beyond the senior-most level, we’ll also see people within organizations take on greater accountability for business and financial performance driven by technology – from the CIO role all the way to individual engineers.
- FinOps Market Consolidation and Integrated Platforms
Prediction 4: The consolidation of the FinOps market is going to pick up speed, leading to a significant shakeout as organizations move away from individual tools and look for more consolidated, all-in-one platforms. 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, optimization and engineering workflows—in one place.
And this shift will increasingly sit under a broader 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.
(Adapted from press release)
