Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Josh Katinger, Principal Product Manager, Data & Integrations, at Intellistack
Enterprise IT has a dirty secret: while we’ve invested heavily in modernizing individual applications and infrastructure, the spaces between those systems remain a mess.
The average team now juggles over ten applications to manage a single project. Each works brilliantly in isolation. Together? A coordination nightmare held together by spreadsheets, manual data transfers, and tribal knowledge that only a few people actually understand.
Quickbase’s 2025 research puts hard numbers to what most IT leaders already feel: 80% of organizations increased their investment in productivity software this year, yet 59% of professionals say it feels harder to be productive than a year ago. Manual work has actually increased for 56% of respondents – despite all that new technology.
We’ve created environments where adding tools creates more work, not less. Here are three predictions for how this plays out in 2026.
Prediction 1: “Workflow Archaeology” Becomes Essential Pre-Work for AI Deployment
Before organizations can deploy AI meaningfully, they’ll need to excavate the undocumented processes holding their operations together. The workarounds. The “just email Sarah” shortcuts. The spreadsheets on personal drives that somehow became mission-critical infrastructure.
Most companies have no idea how much tribal knowledge lives in employees’ heads. In 2026, smart organizations will document these shadow workflows before deploying AI. The ones that skip this step will discover – expensively – that you cannot automate what you don’t understand.
Prediction 2: AI ROI Failures Will Expose the Hidden Work Crisis
Forrester predicts enterprises will delay 25% of their planned AI spend into 2027 as ROI demands tighten. Only 15% of AI decision-makers reported an actual EBITDA lift from their investments in the past year.
The connection most vendors won’t make: AI initiatives are failing not because the models aren’t capable, but because data is trapped in silos and workflows are trapped in people’s heads. You cannot train or deploy AI effectively when critical business logic exists only as institutional knowledge held by employees who’ve been bridging system gaps for years.
Prediction 3: Platform Consolidation Shifts From Cost-Cutting to Strategic Imperative
Zylo reports companies wasted an average of $18 million on unused SaaS licenses in 2023. But the real cost isn’t shelfware – it’s the 11+ hours per week that 59% of professionals spend simply searching for information across fragmented tech stacks. Atlassian estimates Fortune 500 companies alone waste 2.4 billion hours annually just hunting for answers.
The market is responding. Gartner created an entirely new Magic Quadrant – Business Orchestration and Automation Technologies – specifically because enterprises demand unified platforms that address integration chaos. Their prediction: by 2030, 70% of enterprises will consolidate onto a single automation platform, up from just 5% today.
In 2026, consolidation shifts from a cost-cutting exercise to a strategic imperative. The goal won’t be fewer tools for fewer invoices. It will be fewer seams – fewer places where data gets lost and knowledge stays hidden.
The Bottom Line
The organizations that will succeed with AI next year won’t be the ones with the most sophisticated models. They’ll be the ones who first solve the integration problem – who can connect data where it lives and make workflows visible before asking AI to optimize them.
The technology to solve this exists today. What’s been missing is the organizational will to address it. AI investment pressure may finally force the issue.
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ABOUT THE AUTHOR
Josh Katinger is a Senior Product Manager at Intellistack, focused on building products that power business-critical workflows � from data infrastructure and integrations to intelligent document generation.
He currently leads product strategy for data and integrations on the company�s next-generation �Streamline� platform � a ground-up rebuild designed for scale, security, and extensibility. His work spans zero-data-retention integration architecture and the adoption of a third-party iPaaS to support a broader ecosystem of third-party tools.
