In my previous article about AI innovation, I discussed why leaders need a “business strategy first, technology second” mindset.
But a sound strategy is only the starting point. The real test is whether an organization can marshal the budget, talent and focus required to execute it.
That is where many AI ambitions collide with operational reality. Resources are already committed to running the business, maintaining core systems and responding to immediate demands. Turning AI priorities into measurable value requires leaders to deliberately create room for execution.
The AI ambition-execution gap
The Rise of Agentic AI ERP white paper reports that organizations typically spend an average of 91% of their IT budgets maintaining current operations, leaving only 9% for innovation.
At the same time, expectations for AI continue to rise. Boards want to understand the strategy. CEOs are weighing the competitive implications. Employees are looking for better, AI-enabled ways to work. And IT leaders must translate that demand into practical use cases while working within the realities of existing budgets, talent and priorities.
This makes AI execution as much a resource-allocation challenge as a technology challenge. When budget, talent and time are absorbed by day-to-day operations, even a compelling AI strategy can remain stuck on the drawing board.
The opportunity is not simply to add more AI projects. It is to rethink where resources are going, create capacity and concentrate investment on initiatives that can deliver a meaningful business result.
According to S&P Global Market Intelligence, organizations reported scrapping almost half of AI proofs of concept before they reached production. That failure rate underscores the execution gap: identifying a promising use case is not enough without the budget, talent and accountability to carry it into production.
Avoiding that outcome requires more than enthusiasm or experimentation. It requires the execution capacity to carry viable ideas from concept to measurable value. Leaders can build that capacity through three practical moves.
Tactic 1: Reduce operating costs to fund innovation
Begin by examining how much budget is committed to operating and supporting the existing technology environment, and whether every one of those costs is still delivering sufficient value.
There’s a misconception that the journey toward AI innovation begins with a new platform, migration or large-scale transformation program. In reality, it begins by creating bandwidth within existing budget and resources to analyze processes, retrain teams and fund new tools.
That was the starting point for leading consumer goods producer, Ypê.
The company relied on SAP as a critical business platform, but it wanted a practical way to reduce the cost and complexity of maintaining its ERP environment while preserving stability for day-to-day operations.
By turning to Rimini Support™ for SAP, Ypê effectively lowered its annual SAP support costs by 50%, creating the budgetary and operational flexibility needed to pursue broader business priorities. More importantly, the company was able to maintain a stable system upon which they could add Agentic AI capabilities, no costly migrations required.
“AI is democratizing technological innovation and making everything much faster. The traditional ERP model doesn’t fit with that. I don’t have an advantage from ERP alone, but when using ERP plus AI across the enterprise, I now have a major advantage,” said Geraldo Pereira, CIO of Ypê.
Action: Identify recurring software maintenance and operating costs that can be reduced or avoided. Then decide in advance how the reclaimed budget will be reinvested in modernization, automation or AI-enabled business outcomes.
“We’ve experienced many financial and operational benefits by switching from SAP support to Rimini Street. And with Rimini Street’s Agentic AI ERP offerings, our roadmap to transformation has become accelerated.” – Geraldo Pereira, CIO, Ypê
Tactic 2: Redirect talent from maintenance to higher-value work
Funding is only part of the equation. AI also requires people who can redesign processes, govern data, evaluate results and scale what works.
That expertise is difficult to mobilize when internal teams are consumed by maintenance, troubleshooting and upgrade planning. A recent Rimini Street survey of 4,300 C-suite leaders found that 23% of workforce time was spent on ERP maintenance, while 98% said IT talent shortages were affecting their technology vision.
For Ypê, the journey did not stop with stabilizing SAP support. With Rimini Street taking on critical support, Ypê began identifying opportunities to improve processes, simplify work and increase the value of its existing SAP investments without making disruption the price of progress through Rimini Consult™ services.
This is where execution capacity becomes real. When internal teams are no longer tied up managing routine system issues, they can focus more attention on higher-value work: process improvement, automation planning, data readiness and the practical steps required to prepare the business for AI.
Action: Ask, “What higher-value work is our team unable to do because of the resources required to keep this system running?” Use the answer to focus your optimization activities and then redirect the saved time and resources toward AI strategy.
Tactic 3: Make AI earn its place
Enthusiasm can produce a long list of pilots and proofs of concept. But without sustained funding, accountability and executive focus, AI projects can become isolated experiments rather than drivers of business value.
“Companies need to do three things: lower their total cost of operations, improve profitability, and drive enhanced competitive advantage. If a project does not do one of those. At least you should not be doing that project.” – Seth Ravin, CEO and Chairman, Rimini Street, on CNBC’s Squawk Box
Ypê’s path shows a more deliberate progression. After first creating stability through Rimini Support™ and then improving its ERP environment through Rimini Consult™, the company is now exploring the next stage of innovation through Rimini Agentic UX™.
Rather than treating AI as a standalone experiment, Ypê’s journey connects AI-enabled experiences to a broader business progression: stabilize what runs the business, optimize how work gets done and then introduce new capabilities where they can create measurable value. And the results speak for themselves.
“At Ypê, we have several AI projects in the works, but the Rimini Agentic UX™ project has outperformed them all in both speed and expectations,” said Pereira. “It only took one month from start to delivery, and this will help us reduce our approval cycle by 60% and accelerate time-to-value. It’s a great win for our IT team.”
Creating capacity first was key to Ypê’s success. Rimini Agentic UX is most powerful when applied to real business processes, not abstract AI ambition. By moving through support, optimization and innovation in a connected way, Ypê shows how organizations can build toward AI adoption with more focus, less disruption and a clearer line of sight to business outcomes.
Action: Ensure each proposed technology investment meets the test outlined in my previous article, based on advice from Rimini Street CEO Seth Ravin on CNBC’s Squawk Box: AI investments should lower operating costs, improve profitability or build competitive advantage.
Watch the full Squawk Box interview:
Rimini Smart Path™: Creating capacity for the journey
Ypê’s progression reflects the Rimini Smart Path™ in action. The Rimini Smart Path™ provides a practical methodology for moving from AI concept to strategy to execution.
The journey begins by supporting and stabilizing core systems, then optimizing the technology environment to reduce unnecessary cost and effort. That creates flexibility to introduce AI and automation where they can produce measurable value, without making a disruptive migration the prerequisite for innovation.
As Rimini Street President and CEO Seth Ravin said in his CNBC Squawk Box interview, “It’s not AI first. It’s AI last.” The business problem comes first. Process improvement and automation follow. AI earns its place when it is the right tool for achieving a clearly defined result.
AI technology will continue to advance, and access to it will continue to expand. Access, however, will not be the differentiator.
The organizations that convert AI ambition into business value will be those that create the capacity to execute: freeing budget, redirecting talent and concentrating investment on the opportunities that matter most.
The question is no longer simply, “What can we do with AI?” It is, “What can we change now so that our best AI ideas can deliver measurable business value?”
Key takeaways
AI success depends less on access to technology and more on an organization’s ability to fund, staff and focus execution. The strongest AI strategies keep the business outcome first, using automation and AI only where they can deliver measurable value.
