ERP in the age of AI: Is the multi-year program dying? 

Chapter 1: We’ve always done it this way 

ERP has always been one of the most daunting undertakings in the corporate world. The playbook was familiar: select a vendor, mobilize a consulting partner, assemble a program office and prepare for years of disruption. Everyone knew the rules of engagement. 

Large teams of consultants would descend on the business. Workstreams were defined across finance, supply chain and HR. Leadership spent hours in steering committees debating scope and budget. The end goal was clear: get the system live, breathe a sigh of relief and hope the business would cope. 

For decades, this way of working persisted not because it was perfect but because it was the only way that seemed feasible. ERP was too big, too critical, too complex to be delivered any other way. 

Business leaders know what this model really meant: spiralling costs, creeping fatigue and a transformation that often promised more than it delivered. Gartner has found that most ERP programs ran 30% over time and 50% over budget, and ultimately 65% failed to meet their quality goals. This became the ‘cost of doing ERP.’ 

Chapter 2: When ERP was a monolithic giant 

The persistence of this model made sense when ERP was a monolith. In the 1990s and 2000s, ERP was designed to be a single, all-encompassing backbone. Companies standardized their core processes around one giant system, often customizing it heavily to mirror the way the business worked. 

The upside was control. Executives could say, ‘finance, HR and supply chain are all running on one system.’ The trade-off was rigidity. Every tweak required expensive development. Every upgrade felt like open-heart surgery. 

Projects routinely spanned five to ten years. A global manufacturer might spend £100 million over multiple phases, with thousands of people involved. The success metric was binary: either the system switched on or it didn’t. Adoption, business value and agility were secondary. 

Executives accepted this because ERP was seen as infrastructure. Like a factory or a power grid, it was a massive investment meant to last. The pain was tolerated because the system was expected to endure for a decade or more. 

Chapter 3: The SaaS challenge 

The 2010s introduced cracks in this model. Vendors like SAP and Oracle pivoted to SaaS, shifting ERP from a one-off purchase to a subscription service. Twice-yearly releases became standard. New features arrived continuously, whether customers were ready or not. 

This forced leaders into uncomfortable territory. For years, they had customized ERP to fit their businesses. Suddenly, they had to adapt their businesses to fit ERP. The model was flipping. 

Executives felt the tension. The CIO of a global retailer described the challenge of managing quarterly release cycles with a team still wired for decade-long projects; he said, ‘we’re trained to run marathons, now the vendor is asking us to sprint every three months.’ 

SaaS made ERP more flexible in theory. In practice, many organizations clung to the old delivery approach. They still mobilized armies of consultants, still ran multi-year programs, still measured success by go-live. The new pace of ERP collided with old delivery mindsets and the old playbook began to lose. 

Chapter 4: Enter the AI era 

That collision has now reached a breaking point. We are firmly in the AI era, and ERP will never be the same again. 

AI has already transformed how ERP gets delivered. Testing cycles can now be cut by 40%, deployment effort reduced by 20-30% and solution build effort halved. Programs that once spanned three years can now be delivered in 18 months. Costs are reduced by a quarter, quality improves and adoption accelerates. 

The deeper shift is how ERP evolves after go-live. SAP estimates that 70% of S/4HANA’s business value will come from AI-driven optimization, automation and data insight. That means ERP stops being a static system and becomes a living, learning platform. 

Consider a logistics company struggling with volatile demand. In the old world, ERP would provide reports weeks after the fact. In the AI-native world, the ERP continuously ingests real-time data, forecasts bottlenecks and auto-adjusts inventory allocations. What used to take a special project becomes part of the day-to-day system. This is more than efficiency. It repositions ERP as a continuous reinvention engine, constantly aligning the business with its strategy and the realities of its market. 

But here is where nuance is needed. These promises are compelling, but they are not guaranteed. AI maturity varies widely across organizations. Legacy systems, patchy data quality and regulatory constraints remain stubborn barriers. What is transformative in one company may feel like chaos in another. Leaders must separate vendor hype from achievable outcomes. 

Chapter 5: Rethinking ERP investments 

For business leaders, this demands a radical rethink. 

ERP can no longer be justified as a compliance-driven upgrade. Nor can it be treated as a back-office refresh. In the AI era, ERP is a strategic lever, which comes with trade-offs. This demands a different approach to leadership: 

• From full scope to MVP – ERP used to be about the big ‘all in one’ solution. The SaaS shift tried to make the industry pivot to a slimmer MVP approach (remember the famous SAP ‘lean core?’), but old habits prevailed and the MVP became larger over the life of the program. AI will make the shift to smaller, lighter, faster programs with a continuous improvement cycle post-program permanent. 

• From go-live to outcomes – Success is not measured by switching the system on, but by business results meaning faster financial closes, better inventory turnover and improved resilience. However, boards must recognize that these gains may not arrive evenly or immediately. 

• From compliance to resilience – ERP used to be about static design and rigid structures. Now it must flex with volatility: supply shocks, inflation spikes and regulatory shifts. Resilience requires ongoing investment and vigilance. It is not a one-off achievement. 

• From capital project to continuous product – ERP is less like a factory and more like a product line, requiring continual enhancement and governance. Perpetual change can be exhausting. Leaders must balance agility with stability, ensuring that constant iteration does not lead to governance fatigue. 

Leaders also need to change how these investments are framed and funded. Instead of evaluating ERP as a capital project with a defined end point, leaders should evaluate it like they would a product line: what ongoing returns does it generate? How does it improve cash flow, resilience and competitiveness?  

For CFOs, this means holding ERP to the same standard as any other major investment. For example, embedding AI into ERP processes can yield 3-5% productivity gains in finance and supply chain. Even a modest 1% margin uplift on a £1 billion business equals £10 million in annual benefit. That is the language of shareholder value, not IT compliance. 

For CIOs, it means redefining credibility. The measure of success is not whether the system went live; it’s whether ERP is improving P&L, enabling agility and reducing risk. Boards expect ERP to deliver measurable business outcomes, not technical milestones. 

The leaders who get this right treat ERP as an asset, not as an overhead.  

Chapter 6: Continuous change demands new leadership 

This shift doesn’t just alter the business case. It alters leadership itself. 

In the monolithic era, ERP governance was episodic: form a steering committee, deliver the system and disband. In the AI era, governance must be continuous. Boards need to treat ERP the way they treat strategy: constantly monitored, adjusted and refreshed. This requires new leadership behaviors: 

• Agility over rigidity – Leaders must be willing to make quarterly adjustments rather than set a ten-year course. 

• Collaboration across functions – CFOs and CIOs must co-own ERP, aligning technology choices with financial outcomes. 

• Resilience-first thinking – ERP must be positioned not just as efficiency software but as a resilience platform, capable of flexing under shocks – whether supply chain disruption, inflation spikes, or regulatory shifts. 

Equally, leaders must confront the ethical and operational risks of AI. Automated decision-making in finance and supply chain can accelerate insights. It also raises accountability questions when AI gets it wrong. Cybersecurity threats grow as ERP becomes more connected and data-hungry. These risks cannot be ignored. 

A CIO at a consumer goods company put it bluntly: ‘ERP used to be the problem we solved once a decade. Now it’s the muscle we flex every quarter.’ 

Chapter 7: Curiosity as the core skill 

Finally, this transformation reshapes what is expected from people. In the AI-ERP era, the most important skill is no longer deep system expertise. It is curiosity. The ability to explore new features, test new capabilities and continually adapt. 

Twice-yearly releases used to feel disruptive. In the AI era, change will arrive monthly, even weekly. AI copilots will alter how processes are executed. Automation will reshape how teams collaborate. Organizations that thrive will be those where employees see change not as a threat but as a chance to learn. 

This requires new cultural norms. Leaders must reward experimentation, not just compliance. They must encourage continuous learning, not just once-off training. They must create space for employees to ask better questions, not just execute tasks. In short, curiosity has become the defining capability. A workforce that learns fast will outpace a workforce that resists change, even if the latter has deeper experience. 

Conclusion: The leadership choice 

ERP has traveled through three eras: the monolith, the SaaS pivot and now the AI-native revolution. Each era has demanded a new playbook. Only this last one has the potential to shift ERP from a costly burden to a source of competitive advantage. The question is whether leadership is prepared to evolve. It depends on leaders approaching ERP not as a finish line but as an ongoing journey; one that demands curiosity, adaptability and a willingness to grapple with both opportunities and risks. ERP is no longer something you complete. It is something you continually recalibrate. The leaders who embrace this balance, seeing ERP as both a source of competitive advantage and a domain requiring vigilance, will be the ones who thrive in the age of AI.