{"id":63324,"date":"2025-12-12T13:38:17","date_gmt":"2025-12-12T13:38:17","guid":{"rendered":"https:\/\/www.elixirr.com\/en-us\/?p=63324"},"modified":"2025-12-12T14:17:43","modified_gmt":"2025-12-12T14:17:43","slug":"erp-in-the-age-of-ai-how-ai-is-rewriting-the-delivery-pyramid","status":"publish","type":"post","link":"https:\/\/www.elixirr.com\/en-us\/erp-in-the-age-of-ai-how-ai-is-rewriting-the-delivery-pyramid\/","title":{"rendered":"ERP in the age of AI:\u00a0How AI\u00a0is\u00a0rewriting the\u00a0delivery\u00a0pyramid"},"content":{"rendered":"\n
\n
\n

Chapter\u00a01:\u00a0Introduction<\/span><\/b>\u00a0<\/span><\/h2>\n

In\u00a0the\u00a0previous\u00a0article,\u00a0we\u00a0outlined how AI is changing the way ERP is perceived\u00a0and forcing it to become a continuously evolving platform rather than\u00a0a\u00a0singular\u00a0project. This article builds on this premise and\u00a0focuses on how that initial implementation\u00a0of the platform\u00a0could be delivered better,\u00a0faster\u00a0and\u00a0cheaper in the AI age. In the next article of this series,\u00a0we explore\u00a0how organizations set up for the\u00a0continuously evolving platform.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

Chapter 2: ERP Groundhog Day?<\/span><\/b>\u00a0<\/span><\/h2>\n

ERP has always been one of the biggest bets a business can make.\u00a0Every large organization has a story about ERP. Most of them begin the same way\u00a0\u2013\u00a0with a mix of ambition and apprehension.\u00a0The ambition is clear: to modernize the core, to simplify complexity\u00a0and\u00a0to create a platform that can finally keep up with the business. The apprehension is equally familiar: the cost, the\u00a0fatigue\u00a0and the creeping sense that success will be measured simply by\u00a0<\/span>getting through it<\/span>.<\/span><\/i>\u00a0<\/span><\/p>\n

For decades, the delivery playbook has been consistent: large teams, multi-year timelines, spiralling\u00a0costs\u00a0and\u00a0underwhelming outcomes.\u00a0The system was so vast, so customized and so mission-critical that the only option\u00a0seemed to be\u00a0the big, multi-year program. Scale was the safety net.<\/span>\u00a0<\/span><\/p>\n

But the world around ERP has changed. Cloud architectures evolve every quarter. AI is redefining how design, testing and support are done. Yet, many companies still run ERP transformations as if nothing has changed,\u00a0as if the old playbook still applies\u00a0and it\u00a0doesn\u2019t.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

Chapter 3:\u00a0The\u00a0end of the\u00a0old\u00a0playbook<\/span><\/b>\u00a0<\/span><\/h2>\n

The first generation of AI in ERP\u00a0isn\u2019t\u00a0about grand futuristic visions.\u00a0It\u2019s\u00a0about time and cost\u00a0\u2013\u00a0the two things that have haunted ERP for decades.\u00a0Gartner recently noted that\u00a0<\/span>\u2018<\/span>by 2027, more than 70% of recently implemented ERP initiatives will\u00a0fail to\u00a0fully meet their original business goals.\u2019<\/span><\/a>\u00a0It\u2019s\u00a0a sobering reminder that the traditional, scale-heavy model is struggling to deliver.<\/span>\u00a0<\/span><\/p>\n

Meanwhile, vendors and partners are proving that automation can transform ERP delivery fundamentals. In SAP\u2019s ecosystem,\u00a0<\/span>AI-driven\u00a0testing\u00a0and configuration automation through platforms like\u00a0Tricentis\u00a0and\u00a0Signavio\u00a0now routinely reduce test cycles by up to 40%.<\/span><\/a>\u00a0<\/span><\/p>\n

This\u00a0isn\u2019t\u00a0about a one-time project anymore either.\u00a0SAP says 70% of S\/4HANA\u2019s value will come from AI-driven optimization and data insights.\u00a0But that\u00a0won\u2019t\u00a0be achieved if the ERP\u00a0doesn\u2019t\u00a0keep evolving, and the ERP\u00a0won\u2019t\u00a0keep evolving unless the organization\u00a0changes the way it delivers,\u00a0staffs\u00a0and governs ERP.\u00a0<\/span>\u00a0<\/span><\/p>\n

AI\u00a0doesn\u2019t\u00a0remove complexity, but it removes the grind\u00a0\u2013\u00a0the low-value work that has always drained time,\u00a0budget\u00a0and morale. It changes the shape of delivery. The marathon becomes a series of sprints. The focus moves from\u00a0\u2018when do we finish?\u2019\u00a0to\u00a0\u2018what can we improve next?\u2019\u00a0ERP stops being a one-time project and becomes a continuous\u00a0platform.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

Chapter 4:\u00a0A\u00a0tale of\u00a0two\u00a0programs<\/span><\/b>\u00a0<\/span><\/h2>\n

To see this change clearly,\u00a0let\u2019s\u00a0step into the shoes of a \u00a31 billion consumer products company embarking on a core ERP replacement.<\/span>\u00a0<\/span><\/p>\n

The traditional approach begins predictably. The program mobilizes more than a hundred people at its peak. There are\u00a08-10\u00a0workstreams spanning finance, supply chain, HR,\u00a0data\u00a0and integration. A steering committee meets every month to review slides thicker than a magazine. The target timeline is four to five years, with a budget north of \u00a3100 million.<\/span>\u00a0<\/span><\/p>\n

Testing is manual. Documentation fills shared drives. Change management becomes a parallel universe of training decks and comms plans.\u00a0By year three, the business is tired. The program is consuming attention and energy that could be spent elsewhere. Go-live becomes the goal, not the beginning of value realization.<\/span>\u00a0<\/span><\/p>\n

Now picture the same company starting again in 2025, with an AI-first delivery model.\u00a0This time, the structure looks different from day one. The core team peaks at\u00a030-40 people, not 120.\u00a0The profile is different: experienced senior individuals who have lived through the past ways of delivering ERP and\u00a0understand the new way, rather than a small army of juniors who are learning on the job. Roles\u00a0are\u00a0different too;\u00a0It\u2019s\u00a0composed of senior process owners, automation\u00a0specialists\u00a0and data engineers,\u00a0not layers of analysts and project administrators.\u00a0<\/span>\u00a0<\/span><\/p>\n

AI augmentation is embedded into the process and ways of working.\u00a0AI copilots generate and\u00a0validate\u00a0test scripts. Agents automatically detect code conflicts and propose fixes overnight. Training materials are produced directly from the configured system using generative tools, reducing weeks of manual effort to hours.\u00a0Even deployment is smarter: automated data validation cuts conversion testing time in half, and intelligent release orchestration reduces downtime from days to hours.<\/span>\u00a0<\/span><\/p>\n

The program is designed to run for 18 months, not half a decade, with a total cost between \u00a310 and \u00a320 million.\u00a0Go live is just milestone #1 in the journey, not the end point. But the\u00a0real\u00a0result\u00a0isn\u2019t\u00a0just a smaller team or a faster timeline.\u00a0It\u2019s\u00a0a fundamentally different shape of work\u00a0\u2013\u00a0more precise, more\u00a0embedded\u00a0and closer to the business.\u00a0<\/span>\u00a0<\/span><\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n\n

\n
\n
\n
\n

\n Traditional vs AI-first model<\/h2> <\/div> <\/div>\n <\/div>\n \n
\n
\n \"\" <\/div>\n <\/div>\n \n <\/div>\n<\/section>\n\n\n\n
\n
\n

This is not a theoretical scenario. It reflects the structure of ERP programs already underway in industries from consumer goods to manufacturing to utilities. The numbers are real, the roles exist and the impact is measurable.\u00a0<\/span>\u00a0<\/span><\/p>\n

The traditional ERP program is an exercise in endurance.\u00a0<\/span>\u00a0<\/span><\/p>\n

The AI-first model replaces scale with precision\u00a0\u2013\u00a0using automation and intelligence to deliver higher quality, faster, at lower cost.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

Chapter 5:\u00a0The\u00a0tools\u00a0are\u00a0already\u00a0here<\/span><\/b>\u00a0<\/span><\/h2>\n

The most common question executives ask when hearing this story is:\u00a0<\/span>\u2018But is the technology really ready?\u2019\u00a0T<\/span>he answer is yes,\u00a0and\u00a0it\u2019s\u00a0already sitting inside most\u00a0large global\u00a0organizations, not being utilized to its fullest\u00a0potential.<\/span>\u00a0<\/span><\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n\n

\n
\n
\n
\n

\n Tools to use<\/h2> <\/div> <\/div>\n <\/div>\n \n
\n
\n \"\" <\/div>\n <\/div>\n \n <\/div>\n<\/section>\n\n\n\n
\n
\n

SAP has publicly confirmed that its strategic partners, including\u00a0Tricentis, are now fully embedded in RISE with SAP to automate test generation, risk\u00a0coverage\u00a0and validation. This integration allows AI to automatically\u00a0identify\u00a0critical business processes and generate intelligent test assets, reducing migration risk and streamlining go-lives.<\/span>\u00a0<\/span><\/p>\n

Signavio\u2019s\u00a0latest process intelligence features use AI to deliver instant, tailored process and metrics recommendations that accelerate design and improve quality. Combined with\u00a0LeanIX\u00a0for architecture insight and\u00a0Celonis\u00a0for process mining, these tools now provide near-real-time visibility into operational inefficiencies. This is\u00a0a capability unheard of in\u00a0previous\u00a0ERP generations.<\/span>\u00a0<\/span><\/p>\n

Code remediation tools like\u00a0SmartShift\u00a0and\u00a0Panaya\u00a0further reduce manual rework by automatically\u00a0identifying\u00a0and converting legacy custom code. According to vendor case studies, automation can remove up to 80% of manual code adjustment effort in SAP upgrades.\u00a0Change management\u00a0tools like\u00a0WalkMe\u00a0are turning ERP adoption into a continuous learning process\u00a0\u2013\u00a0guiding users contextually within applications, rather than relying on static training courses.<\/span>\u00a0<\/span><\/p>\n

Even AI software vendors are\u00a0getting into the game.\u00a0For example, imagine tagging @Codex in your team\u2019s Slack channel (or Teams) to generate a code snippet or interface stub that aligns to your blueprint, ready for a developer to refine. Codex,\u00a0built by OpenAI to turn natural language prompts into working code,\u00a0already supports deep contextual editing, multi-file\u00a0changes\u00a0and integration\u00a0with\u00a0a number of\u00a0platforms.\u00a0<\/span>\u00a0<\/span><\/p>\n

Microsoft Copilot can make documentation simpler and more usable by enabling knowledge retrieval,\u00a0analysis\u00a0and prediction in natural language.\u00a0For example,\u00a0imagine\u00a0end users being able to ask Copilot questions in natural language and learn how a process is performed without needing a formal training program. This is how we learn now in our daily lives, but we\u00a0don\u2019t\u00a0seem to do it at work (yet).<\/span>\u00a0<\/span><\/p>\n

The\u00a0challenge and opportunity\u00a0now\u00a0lies\u00a0not in invention, but in\u00a0mindset,\u00a0governance\u00a0and\u00a0orchestration. All these technologies are proven and enterprise-grade. The differentiator is how leaders\u00a0shift to this new way of thinking and\u00a0combine them to remove duplication, accelerate\u00a0outcomes\u00a0and\u00a0maintain\u00a0control.<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

Chapter 6:\u00a0Rethinking the\u00a0integrator\u00a0model<\/span><\/b>\u00a0<\/span><\/h2>\n

All of\u00a0this challenges the traditional role of the system integrator.\u00a0For decades, the integrator owned the program. They wrote the plans, staffed the\u00a0teams\u00a0and set the pace. Clients paid for size on the assumption that more people equalled more control.\u00a0<\/span>\u00a0<\/span><\/p>\n

AI changes that equation.\u00a0When testing, code management and change enablement are\u00a0largely automated, the advantage shifts back to the client. Programs can be governed by leaner, more focused structures led by an independent\u00a0business\u00a0integrator,\u00a0a team that oversees design, sequencing and outcomes without vendor or consultancy ties.<\/span>\u00a0<\/span><\/p>\n

The\u00a0SI\u00a0still plays a critical role, but as an execution engine rather than a general contractor. Specialist firms take on targeted roles:\u00a0SmartShift\u00a0handles code remediation,\u00a0Tricentis\u00a0manages test automation, niche providers focus on adoption. The delivery ecosystem becomes modular\u00a0\u2013\u00a0easier to scale, easier to govern and easier to measure.<\/span>\u00a0<\/span><\/p>\n

Clients can and should demand more transparency. Productivity metrics should be visible. Team sizes should reflect scope, not habit. Contracts should reward\u00a0business\u00a0outcomes\u00a0\u2013\u00a0faster closes, better inventory\u00a0turnover\u00a0and\u00a0higher adoption\u00a0\u2013\u00a0rather than hours billed\u00a0or program milestones such as go\u00a0live\u2019s.\u00a0<\/span>\u00a0<\/span><\/p>\n

ERP stops being a black box. It becomes a measurable system of delivery.\u00a0But this requires stronger management and oversight from the client, and\u00a0in some situations calls for an independent advisor or\u00a0business\u00a0integrator to oversee delivery.\u00a0<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

Conclusion:\u00a0A\u00a0different\u00a0kind of ERP\u00a0story<\/span><\/b>\u00a0<\/span><\/h2>\n

ERP has moved through three eras. The first was monolithic: control at all costs. The second was the cloud era: flexibility promised but rarely delivered. The third, now\u00a0emerging, is AI-native: smaller,\u00a0smarter\u00a0and always learning.<\/span>\u00a0<\/span><\/p>\n

Each era has forced leaders to rethink their approach. This one demands the most courage,\u00a0to abandon the comfort of the large program and embrace the discipline of continuous delivery.\u00a0ERP can now be what it was always meant to be: a living system that evolves with the business and delivers measurable value quarter after quarter.<\/span>\u00a0<\/span><\/p>\n

However, do not assume that the tech alone will fix ERP delivery.\u00a0The implicit assumption is that organizations can adopt these tools quickly and that cultural change will follow technology,\u00a0historically the opposite has been true.\u00a0Independent surveys (e.g., Panorama Consulting, 2024) continue to show that most ERP failures are caused by governance and organizational resistance, not tool immaturity.\u00a0In my next article I will go into setting up the team and governance to make this AI-first model successful.<\/span>\u00a0<\/span><\/p>\n <\/div>\n <\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":6,"featured_media":63325,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[116],"tags":[115],"related_service":[81],"related_industry":[],"class_list":["post-63324","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","tag-ai"],"acf":[],"yoast_head":"\nERP in the age of AI:\u00a0How AI\u00a0is\u00a0rewriting the\u00a0delivery\u00a0pyramid - Elixirr - USA<\/title>\n<meta name=\"description\" content=\"Each era has forced leaders to rethink their approach. 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