Most business leaders know the feeling: you’ve invested significantly in a digital transformation initiative — new software, a systems overhaul, a cloud migration — and when someone asks how it’s going, the honest answer is “better than before, but not quite what we expected.” It turns out this experience is nearly universal. And the firms who make a living guiding these transformations are finally being honest about why — and what they’re changing.

The Numbers Tell an Uncomfortable Story

PwC’s 2026 Digital Trends in Operations Survey, which polled 767 operations and supply chain leaders at U.S. companies, surfaced a striking contradiction at the heart of enterprise technology investment today. Eighty-five percent of respondents said they were ahead of most competitors in digital transformation. Yet 89 percent said their technology investments hadn’t fully delivered the results they expected. Both things are true at the same time — which means the bar everyone is clearing is just not very high.

Dig a little deeper and the culprit becomes clear. Only 30 percent of survey respondents reported significant improvement in data quality and reliability following their transformation efforts, and 87 percent said poor data quality had specifically hampered their ability to generate value from digital investments. In other words, companies are buying better tools and wiring them into processes that were already broken — and then wondering why the outcomes fall short.

This isn’t a new observation, but the scale of the documented gap is striking. When the overwhelming majority of companies that have invested heavily in transformation still can’t point to the results they projected, that’s a signal that something structural needs to change — not just in the technology itself, but in how transformation work gets done.

How the Big Consulting Firms Are Responding

The major players in IT consulting have been watching these numbers, and this spring brought a wave of announcements that reflect a genuine retooling of approach — not just new product names.

At its Think 2026 conference in Boston on May 6, IBM unveiled new capabilities within IBM Enterprise Advantage, which it describes as an “asset-based consulting service” designed to help enterprises build and operate their own AI platforms rather than simply license someone else’s. Two tools drew particular attention. Context Studio, available now, lets organizations create AI agents that are grounded in the actual structure of their own data and processes — a direct response to the data-quality problem PwC documented. Process Studio, coming soon, is designed to help businesses convert legacy procedures into what IBM calls “agent-ready workflows” by analyzing existing documentation at scale. In one client engagement previewed at the event, IBM analyzed 1,400 procedures, identified more than 1,000 improvement opportunities, and projected a reduction in operating costs of more than 25 percent over 18 months once agentic AI was applied to the redesigned workflows.

Separately, Deloitte announced the launch of a dedicated end-to-end agentic transformation practice built around Google Cloud’s Gemini Enterprise technology. The move signals that Deloitte sees agentic AI — systems where multiple AI models collaborate autonomously to complete complex, multi-step tasks — as the next organizing principle for enterprise transformation work, not a feature to bolt on later. Meanwhile, EPAM Systems announced a multi-year strategic partnership with Anthropic to deliver enterprise-grade AI focused specifically on safe deployment in complex legacy environments, addressing a concern that many mid-market companies have quietly held for some time: that AI built for consumer applications won’t hold up inside regulated, high-stakes business systems.

From Pilots to Production — What’s Actually Different Now

One of the clearest signals that the transformation conversation is maturing comes from Deloitte’s 2026 State of AI in the Enterprise report, which found that AI tools are now available to the workforce at roughly 60 percent of surveyed organizations. That’s a sharp shift from even two years ago, when AI was largely confined to small experimental teams. A third of those organizations are actively using AI to redesign core processes or create entirely new products and services — not just to automate individual tasks.

The IBM Think announcements put some concrete numbers behind what this can look like in practice. Providence, one of the largest health systems in the United States, worked with IBM Consulting to deploy an AI-powered HR agent integrated into its existing HR platform. After roughly eight months, managers were spending 90 percent less time on hiring steps, and internal caregiver transfers were being completed 12 days faster on average. The cost of those transfers dropped 60 percent. These aren’t pilot-program results — they’re operational outcomes from a production deployment inside one of the most regulated industries in the country.

The pattern here is important for any business leader watching these developments. The companies seeing measurable results from transformation aren’t the ones who bought the most sophisticated software. They’re the ones who used the transformation process to fix the underlying data and process problems first — then layered AI on top of a foundation that could actually support it.

What This Means If You’re Evaluating a Transformation Initiative

If you’re a business owner or executive thinking about a digital transformation project — or trying to figure out why a recent one didn’t land the way you hoped — the current consulting landscape offers some useful pressure-test questions to put to any technology or consulting partner:

• How do you handle data quality before deployment? If a partner is proposing new systems without a concrete plan to address the quality of the data those systems will rely on, the PwC numbers suggest you’re likely to end up in the 89 percent who don’t get full value.
• Are we redesigning the process, or just automating the current one? The IBM case studies and Gartner’s warning that 40 percent of agentic AI projects will fail by 2027 point to the same root cause: automation applied to a broken process just produces broken results faster. Ask specifically how the engagement will identify and fix process gaps, not just digitize them.
• What does success look like after 12 months — in business terms, not technology terms? The shift toward outcome-based consulting models means the best partners are willing to tie their fees, at least in part, to the results they help you achieve. If a partner can’t articulate expected outcomes in plain business language, that’s a meaningful signal.

The Takeaway

The technology available to business owners in 2026 is genuinely more powerful than anything that existed three years ago. But the gap between what transformation promises and what it delivers isn’t primarily a technology problem — it’s a process and data problem that better technology can either solve or amplify, depending on how the work gets done. The consulting firms investing heavily in new delivery approaches this spring are, at some level, acknowledging that the old model — parachute in experts, implement a platform, hand over the keys — isn’t good enough anymore. For any business evaluating a transformation initiative, that acknowledgment is actually good news. It means there are now better frameworks, better tools, and better questions to ask before the first invoice arrives.

If you’re working through a digital transformation initiative or trying to make sense of how AI fits into your operations, the team at Kode Vox is glad to talk through what the right approach might look like for your business. Reach us at info@kodevox.com or through our contact page.

Sources and further reading:

• IBM Consulting Expands AI Capabilities to Accelerate Enterprise Transformation — IBM Newsroom, May 6, 2026
• Deloitte Launches Google Cloud Agentic Transformation Practice — Deloitte Press Room
• PwC’s 2026 Digital Trends in Operations: How AI Reinvents Enterprise Performance — PwC
• EPAM & Anthropic Team Up to Build the Future of Enterprise Transformation with Safe, Applied AI — EPAM Newsroom
• The State of AI in the Enterprise — 2026 AI Report, Deloitte

— The Kode Vox Team