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Apptio Releases AI TCO & Usage and Hybrid IT TCO Impact

Apptio, an IBM company, has announced the availability of AI TCO & Usage and Hybrid IT TCO Impact, two features designed to empower enterprises to take control of their hybrid and multi-cloud strategy and to ultimately drive increased ROI from AI and hybrid IT investments.

With AI TCO & Usage, teams can actively monitor spend and performance across AI initiatives to help drive measurable business value. Hybrid IT TCO Impact provides finance teams with visibility into the financial impacts from migrating applications across hybrid environments. The new offerings join Apptio’s slate of SaaS solutions for Technology Business Management (TBM), which encompasses IT financial management (ITFM), FinOps, and strategic portfolio management (SPM), collectively designed to align organizational IT strategy to business value and outcomes.

To help address potential blind spots in cost visibility, IBM Apptio’s Hybrid IT TCO Impact provides comprehensive cost visibility, enabling companies to track application TCO and unit rates across environments, and adjust strategies to reduce costs and enhance efficiency amid constantly evolving migration needs.

“These solutions are built to fill critical gaps in enterprise TBM, to give organizations greater agility to stay on top of the constantly shifting cloud and AI landscapes,” said Eugene Khvostov, Chief Product Officer, Apptio. “AI TCO & Usage is designed to solve the AI ROI dilemma, and we developed Hybrid IT TCO Impact to support technology decision makers on their overall hybrid cloud strategy. Both solutions are specifically tailored to address some of the industry’s most pressing needs, including IT cost transparency and demonstrating value, and we’re excited to bring them to market.”

AI TCO & Usage enables organizations to track total cost and business impact across AI initiatives, helping them optimize spend, measure outcomes, and scale. With active visibility, users can make more informed investment decisions, enable solution adoption, and maximize the impact of AI across the organization. Additionally, users can:

  • Monitor the lifecycle of their AI investments, providing defensible transparency into ongoing AI costs and usage across AI models and AI solutions.
  • Proactively get ahead of AI sprawl by continuously monitoring AI TCO trends and anomalies, obtaining visibility into detailed cost drivers – cloud, vendor, labor – while surfacing AI usage and user adoption across business units.
  • Drive more informed AI scaling decisions by assessing unit economics and enable responsible AI consumption and show back across their organization.

Hybrid IT TCO Impact is a solution available for IBM Apptio Costing that helps enterprises demonstrate the financial impact of application migrations across their evolving Hybrid IT landscape, featuring:

  • Financial Visibility: Provides a dedicated financial view into application migrations, tracking cost shifts and ROI across the hybrid IT landscape. Informed by this data, organizations can balance costs across cloud and on-prem infrastructure.
  • Single-Pane Management: Unifies on-prem, private cloud, and public cloud footprints into a single view, delivering visibility into the hybrid IT estate.
  • End-to-End Insights: Enables active tracking of migration progress, supporting alignment with broader cloud business and financial goals.

“The growing complexity of cloud deployments and increasing investment in AI are making IT cost optimization an increasingly elusive target,” said Jevin Jensen, IDC research vice president, Intelligent Cloud and FinOps. “TCO features are needed across both public and hybrid clouds to stay on top of the constant changes and plan more proactively.”

Hybrid IT TCO Impact and AI TCO & Usage are both available now.

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Apptio Releases AI TCO & Usage and Hybrid IT TCO Impact

Apptio, an IBM company, has announced the availability of AI TCO & Usage and Hybrid IT TCO Impact, two features designed to empower enterprises to take control of their hybrid and multi-cloud strategy and to ultimately drive increased ROI from AI and hybrid IT investments.

With AI TCO & Usage, teams can actively monitor spend and performance across AI initiatives to help drive measurable business value. Hybrid IT TCO Impact provides finance teams with visibility into the financial impacts from migrating applications across hybrid environments. The new offerings join Apptio’s slate of SaaS solutions for Technology Business Management (TBM), which encompasses IT financial management (ITFM), FinOps, and strategic portfolio management (SPM), collectively designed to align organizational IT strategy to business value and outcomes.

To help address potential blind spots in cost visibility, IBM Apptio’s Hybrid IT TCO Impact provides comprehensive cost visibility, enabling companies to track application TCO and unit rates across environments, and adjust strategies to reduce costs and enhance efficiency amid constantly evolving migration needs.

“These solutions are built to fill critical gaps in enterprise TBM, to give organizations greater agility to stay on top of the constantly shifting cloud and AI landscapes,” said Eugene Khvostov, Chief Product Officer, Apptio. “AI TCO & Usage is designed to solve the AI ROI dilemma, and we developed Hybrid IT TCO Impact to support technology decision makers on their overall hybrid cloud strategy. Both solutions are specifically tailored to address some of the industry’s most pressing needs, including IT cost transparency and demonstrating value, and we’re excited to bring them to market.”

AI TCO & Usage enables organizations to track total cost and business impact across AI initiatives, helping them optimize spend, measure outcomes, and scale. With active visibility, users can make more informed investment decisions, enable solution adoption, and maximize the impact of AI across the organization. Additionally, users can:

  • Monitor the lifecycle of their AI investments, providing defensible transparency into ongoing AI costs and usage across AI models and AI solutions.
  • Proactively get ahead of AI sprawl by continuously monitoring AI TCO trends and anomalies, obtaining visibility into detailed cost drivers – cloud, vendor, labor – while surfacing AI usage and user adoption across business units.
  • Drive more informed AI scaling decisions by assessing unit economics and enable responsible AI consumption and show back across their organization.

Hybrid IT TCO Impact is a solution available for IBM Apptio Costing that helps enterprises demonstrate the financial impact of application migrations across their evolving Hybrid IT landscape, featuring:

  • Financial Visibility: Provides a dedicated financial view into application migrations, tracking cost shifts and ROI across the hybrid IT landscape. Informed by this data, organizations can balance costs across cloud and on-prem infrastructure.
  • Single-Pane Management: Unifies on-prem, private cloud, and public cloud footprints into a single view, delivering visibility into the hybrid IT estate.
  • End-to-End Insights: Enables active tracking of migration progress, supporting alignment with broader cloud business and financial goals.

“The growing complexity of cloud deployments and increasing investment in AI are making IT cost optimization an increasingly elusive target,” said Jevin Jensen, IDC research vice president, Intelligent Cloud and FinOps. “TCO features are needed across both public and hybrid clouds to stay on top of the constant changes and plan more proactively.”

Hybrid IT TCO Impact and AI TCO & Usage are both available now.

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Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

In MEAN TIME TO INSIGHT Episode 21, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses AI-driven NetOps ... 

Enterprise IT has become increasingly complex and fragmented. Organizations are juggling dozens — sometimes hundreds — of different tools for endpoint management, security, app delivery, and employee experience. Each one needs its own license, its own maintenance, and its own integration. The result is a patchwork of overlapping tools, data stuck in silos, security vulnerabilities, and IT teams are spending more time managing software than actually getting work done ...

2025 was the year everybody finally saw the cracks in the foundation. If you were running production workloads, you probably lived through at least one outage you could not explain to your executives without pulling up a diagram and a whiteboard ...

Data has never been more central to a greater portion of enterprise operations than it is today. From software development to marketing strategy, data has become an essential component for success. But as data use cases multiply, so too does the diversity of the data itself. This shift is pushing organizations toward increasingly complex data infrastructure ...

Enterprises are not stalling because they doubt AI, but because they cannot yet govern, validate, or safely scale autonomous systems, according to The Pulse of Agentic AI 2026, a new report from Dynatrace ...

For most of the cloud era, site reliability engineers (SREs) were measured by their ability to protect availability, maintain performance, and reduce the operational risk of change. Cost management was someone else's responsibility, typically finance, procurement, or a dedicated FinOps team. That separation of duties made sense when infrastructure was relatively static and cloud bills grew in predictable ways. But modern cloud-native systems don't behave that way ...