Key Insights and Strategic Imperatives - It's all about selecting the right trains
The inaugural EFESO European Survey on the current state of generative AI reveals a rapid adoption of generative AI tools by procurement organizations across Europe.
Early adopters and fast movers in this transformation will gain a significant competitive edge.
Two decades ago, during the first digital revolution, CEOs and CPOs feared missing the shift from paper to digital. Today, as we stand at the dawn of a new era driven by generative AI, the concern is no longer about missing the train. With countless AI use cases emerging, and 95% of procurement organizations planning to launch generative AI projects in 2025, the real question is: Which trains should we board?
The survey highlights a critical challenge: only 15% of procurement-led AI projects meet their intended objectives. This failure rate is nearly double that of traditional IT projects without AI. The root cause? A lack of experience, coupled with the breakneck pace of generative AI advancements.
To overcome this challenge, organizations must exercise sharp selectivity in choosing generative AI use cases, prioritizing areas with the highest value potential. The study indicates that over 50% of value creation lies upstream in the source-to-contract phase, primarily driven by enhanced performance (35%), increased productivity (39%), and accelerated processes (13%).
Additionally, leaders must proactively address key risks associated with generative AI projects, including data inaccuracy, cybersecurity vulnerabilities, and intellectual property concerns.
A successful generative AI deployment starts with aligning projects to concrete business needs. This requires a clear understanding of AI’s future role within the organization to guide technological decisions, allocate resources effectively, and attract the right talent. The true battleground for AI success lies within the organization’s internal structure and operational alignment.
Leaders must ask: How are our teams organized? What do they need to succeed? By addressing these questions, procurement organizations can unlock the transformative power of generative AI, driving sustainable competitiveness on the global stage.
Gael Sandrin,
Principal
EFESO Management Consultants
Leaders must ask: How are our teams organized? What do they need to succeed? By addressing these questions, procurement organizations can unlock the transformative power of generative AI, driving sustainable competitiveness on the global stage.
Gen AI is already widespread
Reported exposure to generative AI tools, % of respondents
Analysis
Valentina Zardoni
Manager
While 79% of respondents have been exposed to AI, only 31% actively use Generative AI tools for work, revealing a significant untapped potential for harnessing this technology in procurement.
Despite its proven ability to enhance efficiency and support decision-making, Generative AI’s integration into business workflows remains limited. Many users seem to adopt these tools based on personal initiative rather than as part of a structured organizational strategy. This indicates that businesses are still far from fully realizing the transformative capabilities and benefits that Generative AI can offer.
Generative AI holds immense potential to revolutionize procurement by addressing key challenges and inefficiencies. Among the transformative opportunities are:
- Automation of Repetitive Tasks
- Improved Decision-Making
- Enhanced Sourcing Strategies
- Contract Management
Interestingly, 17% of respondents use Generative AI outside of work but not in professional contexts. This highlights a gap in understanding its potential business applications.
Providing targeted training and sharing success stories in procurement-specific scenarios could help this group transition from casual users to advocates for organizational adoption.
GenAI may already be widespread, but its full potential is still waiting to be unlocked!
Everyone wants a piece of the cake
Do you plan to launch Gen AI project in 2025?
Analysis
Martin Kruschel
Senior Partner
Generative AI and its use are hot topics on the management floors of industrial companies worldwide. While surveys just a few months ago showed a great deal of skepticism about AI's benefits, people are currently desperately looking for areas of application. It is not surprising that purchasing and procurement are coming into focus as a major value lever.
The survey results impressively show that almost every company looks into generative AI. No field of application seems too complex or too difficult not to at least test the use of generative AI and thereby generate value.
Company management encourages all CPOs to optimize their business processes through generative AI. The search is on for fields of application and solution providers so as not to miss the AI train.
However, the hunt for ever new fields of application also harbors risks!
Developing a digitalization strategy for the business sector in advance is essential to avoid getting lost in the forest of different AI solutions. Without a strategy, the likelihood of success decreases rapidly.
Like other digitalization projects, generative AI heavily depends on the quality of the available data. Many digitalization solutions have failed and are still failing today due to the insufficient quality of the available data. To address this issue, generative AI can and should first be used to improve data quality before looking for new solutions.
With the increased demand for solutions, solution providers' prices are also rising, especially for individualized and customized solutions. Therefore, an AI implementation project should be prioritized according to the likelihood of implementation and business impact to avoid wasting a lot of money through premature deployment.
Gen AI has the potential to revolutionize the world of work if used correctly. However, the learning curve should be kept as low as possible during implementation.
Value lies on source- to-contract
Where do you see the most value for Gen AI in procurement value chain?
Analysis
Niklas Lübker
Principal
It is amazing how quickly the discussion and understand around Gen AI evolved in the purchasing and procurement world over the last year. Our survey perfectly reflects, what we see in our day-to-day projects, Gen AI can bring the biggest value in the Source-to-contract processes - it has to be as this is usually the most complex task with many stakeholders involved.
If we take a look into the three topics highlighted in the source-to-contract segments, we know that for Supplier Sourcing, Consultation (RfX) & negotiation and Contract Management, the current Gen AI toollandscape looks very diverse and current application have a very good maturity level in each of those segments, with the exception of Gen AI negotiation application for production materials.
But there is not the one fits all solution, nor is there that one application which covers all segments.
Thus, companies have to select the right application, build the right ecosystem with truly connected application, creating significant value-add for the organization by connecting those applications and adjust their processes landscape accordingly to be successful in leveraging Gen AI in the Source-to-contract environment.
But for now, very few Gen AI project succeed
Are you satisfied with the value generated by Gen AI project vs. initial framing and investment?
Analysis
Laurent Coulon
Senior Partner
AI offers unprecedented opportunities for industrial companies: optimizing production processes, improving sourcing and product quality, predictive maintenance, accelerating innovation through the analysis of massive data.
If the competition is on, the results are not necessarily there. According to our study, 85% of AI projects fail. That's almost double the failure rate of a standard IT project (without AI).
Why this alarming statistic? Companies fundamentally lack experience and hindsight. In their defense, the technological revolution of generative AI has been lightning-fast. And it goes far beyond the technical and IT framework.
That's why new methods are needed to keep up with the times, and that's often where the problem lies.
Inaccuracy, cybersecurity, and intellectual-property infringement are the most-cited risks of generative AI adoption
Generative AI–related risks that organizations consider relevant and are working to mitigate, % of respondents.
Analysis
Marc Irmler
Manager
Generative AI is rapidly emerging as a transformative force in today's global marketplace, offering procurement teams a powerful lever to unlock operational efficiencies and create outsized value for the business.
Despite its promise, many organizations have been slow to address the inherent risks associated with AI-powered tools - such as inaccuracies, cybersecurity threats and intellectual property disputes - creating blind spots that can erode stakeholder trust and undermine performance.
This underscores the importance of implementing a holistic governance framework that embeds rigorous risk assessments across the entire procurement lifecycle, enabling executives to protect against the dimensions of risk. In parallel, by fostering cross-functional collaboration and integrating responsible AI practices into broader digital transformation initiatives, procurement teams can create sustainable impact, achieve measurable cost efficiencies and maintain future-ready capabilities.
Performance, Speed and lightness are top objectives
Top objective for organizations’ planned generative AI activities, % of respondents
Analysis
Corentin Chaix
Senior Consultant
The industry is undergoing a radical transformation in a highly evolutionary tech landscape and a very volatile geo-political environment, playing with increasing regulatory constraints making the task harder.
To face up, Gen AI is establishing itself as an essential lever to make organizations more agile, more productive, and above all, faster.
The survey results clearly show the trend toward what Gen AI was developed for: improving End-to-End business processes, spanning across operations, customer services, and back-office functions. The aim is to increase the speed of execution, chasing out complexity everywhere, pushing on innovation, learning from industry competitors, copying what works.
Generative artificial intelligence is forcing a paradigm shift for organizations: to reinvent the industry, we need to reinvent ourselves.
Business not in front line and talent deficit poses the biggest challenge
Element that poses the biggest challenge in capturing value from AI, % of respondents
Analysis
Kenneth Sievers
Partner
The unveiling of ChatGPT in late 2022 marked a pivotal moment in technological evolution, that is revolutionizing industries and transform the way businesses operate, leading to increased efficiency, productivity and growth.
Since then, at the latest, companies have been concerned with how they can leverage AI technologies for themselves and what added value it can bring to them. Our survey reveals and confirms what we often see in practice.
The two biggest challenges to capture value from AI:
First, Digitization and AI are too often developed from a strong IT perspective, without putting the actual beneficiary, the business, at the center of considerations and thus also bringing them into the lead, as product owners, of AI projects. Identifying the right use cases is key: determining where AI can add the most value is not always straightforward. Businesses need to carefully assess which processes and functions will benefit most from AI implementation. This can best be judged by the respective business department.
The second biggest challenge is about talent and skill sets: many organizations struggle to find employees with the necessary AI expertise. Bridging this skills gap requires significant investment in training and hiring.
At EFESO Management Consultants, we focus on exactly these two challenges. We support our partners in bringing the business to the forefront and bringing the necessary AI and technology expertise to the table.
