IBM TM1, Agentic AI & Finance Transformation Insights

The Model Context Protocol (MCP) is evolving from a developer-focused protocol for connecting AI models with tools and data into something much closer to production infrastructure for agentic applications. On July 28, 2026, the MCP team released the 2026-07-28 specification, introducing one of the biggest architectural changes since MCP launched: a stateless protocol core. The release also brings Multi Round-Trip Requests (MRTR), header-based routing, cacheable list responses, stronger authorization, a formal extensions framework, and updated Tier 1 SDKs. For teams building AI agents and MCP ...

Beyond Basic Export: Real-Time TM1 to Power BI Integration using Datafusion A while back, we published a guide on integrating Power BI and TM1. The premise was straightforward: business leaders want the heavy-lifting, industrial-grade modeling of Planning Analytics combined with the accessibility and visual engine of Power BI. You build your complex, multi-entity financial logic in TM1, and you present it beautifully in Power BI. It is the right architecture. But honestly—for a long time—the mechanics of actually connecting the two systems have been less than ideal. If you manage an ...

At our recent CFO roundtables in Perth and Melbourne, one theme surfaced faster than any other: governance isn't a nice-to-have for finance AI projects, it's the reason most of them stall. Finance teams don't operate under the same rules as the rest of the business. Data handling in finance carries obligations most other functions never have to think about — audit trails, regulatory reporting, materiality, segregation of duties, and a level of scrutiny that assumes every number will eventually be checked by someone whose job is to find the problem. That's a very different starting point to a ...

Over the past few weeks, Octane Solutions ran AI roundtables with finance leaders in Perth and Melbourne. No decks, no slideware, no "AI 101." Instead, we sat down with CFOs and their teams, showed them real AI models solving real finance problems, and let the conversation go wherever it needed to go. That last part mattered more than we expected. These sessions weren't a pitch delivered at finance executives — they were a conversation with them. And what came back was some of the most candid, useful feedback we've heard on where finance actually stands with AI today. The format: show, don't ...

The third theme from our Perth and Melbourne CFO roundtables was the one every finance leader recognised instantly: Copilot is already in place, it's genuinely useful — and it hasn't moved the needle on the business. Copilot works. It just isn't wired into finance Almost every finance team we spoke to has Copilot rolled out. People use it to draft emails, summarise documents, get a first pass at a memo done faster. Nobody in the room disputed that it helps. What nobody could point to was a case where it changed how the finance function actually operates. The reason came up repeatedly once we ...

1. Introduction Selector tiles in PAW help convert a normal cube view into a client-friendly dashboard control. Instead of asking users to open dimensions or manually change the cube context, they can simply click a tile such as Version, Year, Month, Entity, or Scenario and see the report change immediately. This helps me change the dashboard view quickly while keeping the layout clean. The same selector can control a cube view, chart, or other synchronized object, so clients can move between summary and detailed views without changing the underlying cube structure. When used with hierarchies ...

When your finance team spends more time wrestling with data than analysing it, your planning software is working against you. For enterprise transportation and fleet operations leaders, selecting the right planning analytics software directly affects everything from route optimisation decisions to fuel cost forecasting. This guide walks you through the evaluation criteria, integration requirements, and automation readiness factors that matter most when choosing a platform for IT-led financial planning. The planning analytics market has matured significantly. According to Gartner Peer ...

The Multi-Agent Orchestration Cortex: Restructuring Month-End Close and Financial Workflows with IBM watsonx Orchestrate Look—if you have spent the last ten years leading an enterprise finance team, you know the physical toll of month-end close. It is 1:00 AM on a Tuesday, and your senior analysts are still hunched over screens, manually stitching together CSV dumps, hunting for broken VLOOKUP links, and copy-pasting numbers between siloed ERPs and legacy reporting tools. Honestly, the problem isn’t that your team lacks capability. The problem is that the underlying operational model is ...

How IBM's June 2026 platform update brings centralized governance, live scheduling, a reusable agent catalogue and tighter data protection to enterprise AI operations Introduction IBM watsonx Orchestrate's June 2026 mid-month release marks a shift in emphasis. Earlier releases were largely about giving builders more ways to construct agents — document extractors, flow controls, prebuilt connectors. This release is about what happens after the agents are built: how they are governed, secured, monitored, scheduled, shared and protected once they are running in production. The headline additions ...

What the latest data from McKinsey, Gartner, Forrester, IBM, PagerDuty and the World Economic Forum actually show about where enterprise AI stands in mid-2026 — and where the gap between ambition and execution remains widest. Introduction Every enterprise now has an AI story. The harder question — the one a business analyst is actually paid to answer — is whether that story is producing value and for whom. Three years into the generative AI boom, the data finally exists to separate the pattern from the noise: how many organizations have moved past pilots, how many are actually running ...

Part 1: Essential Functions Every TM1 Developer Should Kno MultiDimensional Expressions (MDX) is one of the most powerful features available in IBM Planning Analytics Workspace (PAW). While many TM1 developers rely on static subsets, mastering MDX opens the door to dynamic reports, intelligent dashboards, and significantly reduced maintenance In this first article of the series, we'll explore three fundamental MDX functions that every TM1 developer should understand: TopCount() Filter() Descendants() These functions form the building blocks of many real-world PAW applications. Why Learn MDX? ...

Evaluation of TM1 Support Models Unified Managed Services A fluid capacity model combining development and support resources. Primary Goal Total Cost of Ownership optimization Key Paradigms Break-fix, Pyramid Staffing, Unified Hybrid I've managed enterprise finance models for a decade, and I just realized this about IBM Planning Analytics (TM1) support: we treat it like insurance when we should be treating it like an engine. When your environment breaks during month-end close, the stress is immediate. But the way most finance teams try to solve this structural risk usually falls into two ...