AI's Impact on Digital Transformations and ERP Implementations

In the latest episode of our Transformation Ground Control podcast, I had the pleasure of speaking with John Belden from UpperEdge, LLC about a hot-button topic in today's digital world: how artificial intelligence (AI), particularly generative AI, is impacting digital transformations and ERP implementations. While AI has already been integrated into operational technologies, John and I focused on the less-discussed area of how AI is transforming the procurement process, system integrator relationships, and the overall structure of ERP implementations.

This conversation opened the door to new and exciting opportunities for organizations looking to leverage AI in their digital transformation journeys. In this blog post, I’ll share the key insights from our discussion, unpack the evolving role of AI in ERP and procurement, and discuss how organizations can prepare for the next wave of AI-driven change.

You can also watch the full interview in this podcast episode:

The Current AI Landscape: Beyond ChatGPT

A central theme that John and I discussed was the misconception that AI is only about tools like ChatGPT. While everyday AI applications such as chatbots and automated assistants are valuable, generative AI’s real potential lies far deeper, especially in complex enterprise operations like ERP implementations.

Many organizations are still dipping their toes into AI, experimenting with tools like ChatGPT and similar platforms. However, as John pointed out, these tools represent only a fraction of what AI is capable of. For instance, generative AI can play a crucial role in optimizing back-office operations, streamlining procurement processes, automating data analysis, and providing predictive insights across various business functions.

In UpperEdge’s experience, the rapid adoption of generative AI by IT service providers and vendors means that organizations need to be equally prepared. AI is being used to assist in software sales, automate project management, streamline procurement, and even aid in negotiations. This means that the buying side—the CIOs and procurement teams—must also arm themselves with AI-driven tools to maintain leverage.

John laid out seven critical challenges and considerations for CIOs and procurement teams as they navigate this AI Revolution:

1. Procurement Process Evolution

The procurement landscape is rapidly evolving, and if you're not adapting your processes to include AI tools, you risk falling behind. Vendors are already utilizing AI to streamline their offerings, which puts buyers at a disadvantage if they don't do the same. From automating the Request for Proposal (RFP) process to using AI-driven analysis to compare complex vendor proposals, procurement officers now have more tools than ever before to make smarter, faster decisions.

AI’s ability to comb through large datasets in real-time allows procurement teams to identify risks, inefficiencies, and opportunities for savings. Organizations that fail to adopt these technologies risk being outpaced by competitors who are leveraging AI to gain an edge in negotiations and vendor management.

2. Understanding AI Terminology

One of the biggest challenges for IT procurement teams is understanding the new terminologies, technologies, and services related to AI. Given that AI is a relatively new field, many organizations are still getting up to speed on how to effectively engage with AI-driven vendors. The key here is education—ensuring that your team understands not just what AI is, but how it can be implemented effectively across the enterprise.

3. Systems Integration Will Evolve

Major systems integrators like Accenture, PwC, and EY are investing billions into AI technologies to optimize their service delivery. This means that the ERP implementations of today will look very different in just a couple of years as AI plays a bigger role. For example, AI can automate previously labor-intensive tasks, such as writing test scripts, performing data migration, or configuring systems. In addition, AI can assist in real-time monitoring of project performance and detect potential issues before they escalate.

The systems integration space is on the cusp of a major transformation, with AI playing a central role in how projects are planned and executed. John and I agreed that organizations that start preparing now will be better equipped to capitalize on these advancements.

4. Risk Management

Managing AI-related risks—both internally and with external vendors—will become essential. Procurement officers need to understand the risk profiles associated with AI, including how it may impact project outcomes. This means assessing not only the technology itself but also the risks that come from relying on vendors who are increasingly embedding AI into their products and services.

As John highlighted, it's crucial to keep in mind that AI tools are not infallible. Even the most advanced AI systems may only be correct 93% of the time, meaning that 7% of the time, the results could be flawed or misleading. This presents a unique challenge in high-stakes environments where accuracy is critical.

5. Regulatory and Privacy Concerns

AI introduces new challenges in terms of compliance, privacy, and regulation. Many countries are introducing regulations that govern how AI can be used, particularly when it comes to personal data. Companies must keep a close eye on evolving AI regulations and ensure that their technology and processes comply with new laws. This is especially true for industries such as healthcare, finance, and government, where data security and privacy are paramount.

6. Leveraging Vendor AI Improvements

AI will drive productivity improvements on the vendor side. As a buyer, it’s essential to find ways to pull those savings through to your own business, ensuring that vendors pass on the benefits. For example, if a system integrator is using AI to streamline their project delivery, they should be able to offer more competitive pricing or faster turnaround times. Organizations need to negotiate AI-driven benefits into their contracts, ensuring that they capture the value generated by their vendors' AI investments.

7. The Importance of Strategic Partnerships

AI is too big for any one organization to tackle alone. Building strategic partnerships with vendors who are proficient in AI can help businesses navigate this complex new landscape. Companies need to choose partners who not only understand the technical aspects of AI but who can also help guide their AI strategy in alignment with their overall business goals.

AI’s Impact on Procurement

One of the most significant areas of impact that John and I discussed is how AI is changing the procurement process. Historically, procurement was a manual process, involving an in-depth analysis of vendor proposals, negotiations, and risk assessments. Now, AI is starting to take over some of these functions, offering procurement officers more tools to make data-driven decisions.

AI can quickly compare multiple vendor proposals, highlighting the similarities and differences that may not be obvious to the human eye. It can assess these proposals for risks, gaps, and compliance with RFP requirements. According to John, this can dramatically reduce the cycle time required for evaluating proposals. AI can also suggest negotiation strategies based on historical data and patterns, giving procurement teams a powerful tool to maintain leverage in negotiations.

However, there’s a caveat. While AI can significantly enhance procurement processes, it’s essential to recognize that current AI tools are not flawless. John pointed out that even in the best-case scenarios, AI is right about 93% of the time. This means that 7% of the time, AI-generated insights may be flawed or inaccurate, which could have serious implications in high-stakes negotiations.

Therefore, it’s crucial to maintain human oversight and ensure that any AI insights are thoroughly vetted before being acted upon.

AI and Systems Integration: A New Era for ERP Implementations

The next big area of impact is on systems integrators and ERP implementations. John shared how companies like Accenture, PwC, and EY are investing heavily in AI to enhance their service offerings. These firms are embedding AI into their ERP implementation methodologies, allowing them to deliver services more efficiently.

For example, generative AI is being used to automate coding, testing, and even training development. Traditionally manual tasks, such as writing test scripts or conducting manual code reviews, are now being done by AI, which frees up human resources for more complex, value-added tasks.

Moreover, project and program management are becoming more streamlined thanks to AI. These tools can analyze project documentation, identify potential risks, and summarize key points for decision-makers, reducing the workload for project managers. By integrating AI into these critical processes, organizations can reduce human error, speed up project timelines, and ultimately improve the overall quality of their ERP implementations.

The Role of Data in AI-Driven Procurement

While discussing AI’s impact on procurement, it’s crucial to understand the foundational role that data plays in making AI successful. AI is only as good as the data it has access to, and organizations must ensure that their data governance, data quality, and data management practices are robust.

John emphasized the importance of data pre-processing—ensuring that data is clean, standardized, and properly categorized before being fed into AI systems. This is particularly relevant in procurement, where vendor data, financial data, and market information must be aggregated and analyzed. Without accurate data, AI-driven procurement strategies will falter, leading to poor decision-making and potential financial losses.

Additionally, organizations need to invest in real-time data collection and integration. AI can provide much more value when it has access to up-to-date information. In the context of ERP systems, AI can leverage real-time data to predict supply chain disruptions, forecast customer demand, and optimize production schedules.

Preparing for AI in ERP: What Organizations Need to Know

So how can organizations prepare for the next wave of AI-driven change? According to John, the key lies in what he calls "Phase Zero." Before diving into an AI implementation, organizations need to carefully plan and strategize. This is especially important because AI is not a one-size-fits-all solution, and different parts of the business may require different AI applications.

During Phase Zero, companies need to:

• Assess their AI readiness: Understand where in the organization AI could have the most significant impact. Conduct an internal assessment to determine how ready the current infrastructure, culture, and skill sets are for AI adoption. This will help create a tailored roadmap for AI implementation.
• Decide whether AI will be used in products or processes: Determine whether AI will be embedded in customer-facing products or used internally to improve business processes. Some organizations may choose to integrate AI into their products to enhance customer experience, while others may focus on using AI for operational efficiencies, such as automating data entry or optimizing procurement cycles.
• Manage non-strategic uses of AI: Just like the rise of end-user computing in the 1990s, AI will likely be adopted by individuals across the organization. IT leaders need to ensure that these non-strategic uses of AI don’t spiral out of control and create risk. Organizations must establish governance frameworks to ensure that AI experiments across departments are monitored and managed effectively.
• Understand the balance between savings and accuracy: While AI can create efficiencies, its results are not always 100% accurate. Organizations need to weigh the trade-offs between cost savings and the potential for inaccurate data. When implementing AI, it’s essential to have processes in place to validate AI-generated insights before making critical business decisions.
• Mitigate AI-related risks: From regulatory compliance to data privacy concerns, organizations need to be proactive in identifying and mitigating the risks associated with AI. This may include building in fail-safes, conducting rigorous testing, and ensuring that AI applications adhere to legal and ethical standards.

What’s Next for AI?

In our discussion, John predicted that the pace of AI innovation may eventually slow down due to the enormous investments that have already been made. Companies will need time to recoup their investments, and regulatory frameworks are likely to become more stringent, slowing down the adoption of new AI technologies. However, that doesn’t mean AI innovation will stop altogether—it will simply become more focused on solving specific business challenges.

Here are a few key trends and advancements that we expect to see in the AI space over the next few years:

1. Improved Accuracy and Reliability

One of the most significant advancements on the horizon is improving AI’s accuracy. Currently, many AI systems provide correct results about 93% of the time, but there’s still a 7% margin of error. For AI to become more widely trusted, that margin of error needs to shrink. As AI models become more sophisticated, we expect to see better validation mechanisms, which will improve the reliability of AI-generated insights.

2. Specialized AI Models

Rather than relying on one large, general-purpose AI system, we anticipate the rise of specialized AI models that are tailored to specific industries or business functions. For example, in ERP, you might see one AI model dedicated to optimizing the supply chain, another focused on financial forecasting, and yet another designed to improve customer relationship management. This specialization will enable businesses to get more precise and actionable insights from their AI systems.

3. New ERP Vendors with AI-Driven Solutions

John believes that a new wave of ERP vendors may emerge, offering fully configurable, AI-driven systems that can be tailored to an organization’s unique processes. This would mark a significant departure from today’s template-based ERP systems, which often require businesses to adapt their processes to fit the software.

With AI-driven ERP platforms, businesses could simply input their requirements, and the system would configure itself based on the organization’s specific needs. This could represent the next major evolution in ERP, as companies would no longer have to compromise their processes to fit within rigid software templates.

4. AI-Enhanced Consulting Services

Consulting firms are already investing heavily in AI, but as their AI capabilities mature, we expect to see a shift in how they deliver services. Rather than relying solely on human expertise, consulting firms will increasingly use AI to provide insights, recommend strategies, and streamline project management. This hybrid approach—combining human judgment with AI-driven analytics—could lead to faster, more cost-effective consulting services.

Conclusion: The Future is AI-Driven

AI is already transforming the world of ERP and digital transformation, but we’re still in the early days. As John Belden highlighted, organizations that start planning for AI now—especially by focusing on procurement, systems integration, and risk management—will be better positioned to succeed in the years ahead.

The takeaway here is clear: AI isn’t just about chatbots and automation. It’s about rethinking how we approach digital transformation from the ground up, using AI to drive efficiency, improve decision-making, and ultimately create more value for the business. Organizations that embrace AI now will be able to harness its power to create competitive advantages, improve internal operations, and deliver better customer experiences.

As AI continues to evolve, it will open new doors for innovation in ERP and digital transformation. By preparing today—through education, strategic planning, and building the right partnerships—organizations can ensure that they’re ready to capitalize on the next wave of AI advancements. While the journey may be complex, the potential benefits of AI are too significant to ignore.

Whether it’s streamlining procurement, enhancing system integration, or improving project management, AI is poised to reshape the business landscape in ways that we’re only beginning to understand. The key for organizations is to take action now, preparing for the future while remaining flexible enough to adapt to the ongoing evolution of AI technologies.