Large-scale enterprises are caught in a paradox of progress.
While interest in artificial intelligence (AI)-powered digital workplaces has reached a fever pitch, actual deployment is lagging as IT leaders collide with the harsh reality of fragmented data and security risks.
Three-fourths of IT leaders are eager to adopt AI-powered digital platforms, yet only 25% have successfully integrated them, according to a new study conducted by Forrester Consulting on behalf of Simpplr.
The so-called “ambition gap” suggests that while the promise of AI is high, the foundational infrastructure of the modern office is not yet sturdy enough to support it.
The primary roadblock isn’t the sophistication of AI models, but the chaotic state of internal data. “AI is revealing how fragmented the digital workplace is,” Simpplr CEO Dhiraj Sharma said. “You can’t scale AI if your digital workplace is disconnected.”
The study found 45% of failed AI initiatives stem from a lack of organizational context. Without a unified data ecosystem, AI agents cannot understand the nuance of specific company workflows. Consequently, 85% of respondents agree that unifying disparate data sources is now a nonnegotiable prerequisite for success.
Even as organizations attempt to bridge data gaps, they are hitting a second wall, that of governance. Although more than 60% of companies have documented AI strategies, nearly half admit they struggle with observability.
Security remains the single most cited concern.
Nearly half of IT leaders identify data leakage and access control as their top anxieties. Indeed, as AI moves from isolated pilot programs to agentic systems, the risk of sensitive information falling into the wrong hands grows. Nearly 80% of leaders say they require more robust security frameworks before they can safely scale.
Compounding these challenges is an explosion of unstructured data like email, chat transcripts, and medical images that make up the bulk of corporate knowledge.
The 2026 State of Unstructured Data Management report by Komprise reveals that 74% of enterprises are now managing over 5 petabytes of this data, a 57% increase since 2024.
“Managing this data using the methods and tools of ten years ago is no longer viable,” said Krishna Subramanian, co-founder of Komprise.
The report highlights that classifying and tagging this data has become the top technical challenge for AI preparation, jumping from 41% to 56% in just two years.
Despite these hurdles, the goal remains operational excellence rather than immediate revenue. Roughly 65% of IT leaders are prioritizing AI to boost employee productivity and automate routine tasks, such as searching for information.
To get there, the industry is seeing a massive shift in human capital and spending. Approximately 40% of organizations are increasing IT budgets specifically for AI, with a heavy focus on hiring infrastructure leaders who can build the AI foundation that today’s fragmented workplaces currently lack.
