Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Sarkis Kalashian, VP of Product Management, Smartsheet
The enterprise software landscape is at an inflection point. For years, organizations adopted AI to speed up work and automate repetitive tasks. Yet many still struggle to translate those capabilities into consistent, reliable value. As 2026 approaches, the question is no longer whether AI can generate output. It is whether it can meaningfully elevate how teams work and how products evolve. AI is shifting from novelty to necessity. What comes next is a transformation in how systems learn, how they earn trust, and how they shape the future of modern work and project execution. In the year ahead, these shifts will fundamentally reshape expectations for enterprise technology.
Products will be taught, not just designed
Software is moving from static interfaces to intelligent systems that learn from the people who use them. In 2026, the most successful products will not simply be designed – they will be taught. Teams will guide AI agents the way they configure dashboards or workflows. These systems will observe patterns, identify friction, and adapt in real time.
Instead of locking in a single “best practice,” AI will learn company-specific practices and improve them over time. Workflows, project plans, and resource structures will evolve dynamically, narrowing the gap between product and process as software becomes an active participant in the work itself.
For product teams, this shift demands designing systems that continuously learn, where feedback cycles that once took weeks become minutes. AI won’t just help users complete tasks; it will help products grow with them. At Smartsheet, we’re already seeing teams gravitate toward tools that learn their unique operational nuances rather than forcing them into rigid templates, a signal of where enterprise expectations are heading.
Trust will become the defining feature of enterprise AI
The first wave of generative AI brought tremendous excitement and also fatigue. Many organizations experienced inconsistent recommendations, unclear reasoning, and variable output quality. In 2026, enterprises will expect AI systems to be transparent, reliable, and grounded in responsible design. AI can no longer exist as a ‘black box’ add-on. It must be accountable.
Enterprise buyers will increasingly demand clarity about how AI reaches conclusions and what data informs decisions. Whether a system recommends resource allocations, flags risks in a project timeline, or applies governance rules, visibility and control will matter as much as speed.
Teams won’t rely on AI that behaves unpredictably. They will adopt tools that explain their reasoning, support human oversight, and align with organizational standards. Vendors that treat governance and transparency as core product features will lead the next chapter of enterprise AI, particularly as companies tighten their data controls and harmonize governance across cloud and hybrid environments.
AI fatigue will push organizations toward higher standards of quality
Many teams are now experiencing what some describe as “AI slop,” content and insights that add noise instead of clarity. In 2026, organizations will respond with higher expectations and stricter internal guardrails. Enterprises will aggressively consolidate tools, reinforce responsible-use frameworks, and prioritize AI that reduces cognitive load.
Success will shift from frequency of use to quality of outcomes. The core questions will be: Does AI accelerate clarity? Does it reduce rework? Does it support better decisions?
For work management platforms, this means building capabilities that elevate human judgment, not overwhelm it. The winning products will be the ones that deliver fewer, better recommendations that teams can act on with confidence. This will be especially true as AI becomes more deeply embedded in the systems that power modern work, from cloud orchestration to resource planning to portfolio-level risk visibility.
AI will shift from summarization to orchestration
The shift from summarization to orchestration is the death of ‘passive AI’; the new standard for work management is predictive- it’s a technology that anticipates risks and coordinates actions before a human even has to ask.
This evolution is especially important in project and portfolio management, where delays often stem from ambiguity and limited visibility. AI that can anticipate risks, recommend adjustments, and keep work moving will deliver meaningful value.
Instead of describing what happened, AI becomes part of how teams decide what happens next. This strengthens the partnership between humans and technology: AI accelerates execution while humans direct strategy. As enterprises distribute workloads across increasingly hybrid and cloud-native architectures, orchestration will become essential for maintaining alignment and momentum.
Human judgment will become more valuable as AI matures
As AI takes on more routine work, human judgment and decision-making becomes the ultimate premium.. While technology will accelerate execution, only humans can provide the strategic or nuanced context required to turn those actions into real impact.
The leaders who thrive in 2026 will be those who can interpret AI-generated insights with confidence and make informed decisions quickly. Across industries, the rise of AI is elevating the importance of critical thinking, creativity, and cross-functional awareness. Technology can accelerate action. Humans ensure that action creates impact.
And for leaders, our role is evolving as we speak, becoming a strategic orchestrator who bridges the gap between vision and execution. We will be expected to move beyond mere experimentation with AI and focus on measurable enterprise outcomes.
A more mature AI era begins
The coming year won’t simply bring more automation. It will bring AI that integrates into work in ways that are reliable, interpretable, and genuinely helpful. The future of enterprise products isn’t about faster output; it’s about smarter, more transparent systems that evolve responsibly and support the teams who depend on them. By 2026, enterprise AI will be defined not by novelty, but by accountability, adaptability, and measurable business impact.
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ABOUT THE AUTHOR
Sarkis Kalashian is the Vice President of Product Management at Smartsheet, where he helps lead the vision and strategy for the company’s AI-powered Intelligent Work Management platform. With more than 15 years of experience shaping enterprise software products, he focuses on building systems that help organizations navigate complexity, improve execution, and adapt to change in real time. He graduated from the University of California, Berkeley.
