How ProcureTech Solution Provider Commentary on Agentic AI Downsides Differs from Procurement Industry Experts and Analysts

Posted on April 21, 2025

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What is the difference between ProcureTech sales and marketing content and the procurement industry experts’ and analysts’ assessment of ProcureTech?

It seems like a reasonable question. However, over the past decades, layers of complexity have muddied the waters of a clear and concise answer. At no other time has the above-referenced complexity been more prevalent and evident than in today’s AI-hyped world.

In my previous post, “What is not being said about Agentic AI? ” I focused on the apparent disconnect between what ProcureTech solution providers are saying about AI and what industry leaders are saying. In raising this difference, I do not suggest anyone deliberately attempts to mislead. However, there is a noticeable chasm between what AI, Generative AI, or Agentic AI can and cannot do.

Hopefully, today’s post will help to bridge that chasm and achieve a more balanced understanding of the roles and objectives of sales, marketing, industry experts, and analysts.

Who Said It (Sales & Marketing or Industry Expert and Analyst):

Jon – you are asking the wrong questions. Procurement will not achieve its ambition or potential without digitalisation. For every single company and person that is championing digitalisation either personally or as part of a team I believe that we should all be advocating for and helping them to succeed rather than speculating on their failure.

It is your and our collective responsibility to change the (wrong) narrative and focus on accelerating the positive. Time is short.

So, who said it? ProcureTech sales & marketing or procurement industry expert and analyst?

Source: ProcureTech CEO Younger stresses we must change the negative narrative and focus on accelerating the positive. – Procurement Insights, November 9th,2024

Not What, But When

Given the recent news that ORO Labs acquired Lance Younger’s ProcureTech 100 company on March 18, 2025, it would be fair to suggest that Lance’s words are well within the enthusiastic boundaries of a sales & marketing narrative.

I am not alone in my concern that Lance made the above statement this past November 2024, when the general view was that ProcureTech 100 was an independent expert and analyst source for many in the procurement industry.

In all fairness, as the table below demonstrates, ProcureTech 100 was not established to be an independent knowledge source like Gartner or other industry analyst firms.

AttributeProcureTech 100Gartner (for comparison)
Primary RoleCurator of top innovative procurement solutionsMarket analyst and evaluator of enterprise tech
Selection MethodCollaborative (with Kearney) and ecosystem-drivenIndependent research, client surveys, vendor analysis
Commercial ModelCommunity platform with partnershipsSubscription-driven, vendor-neutral (in principle)
Evaluation TransparencyLimited methodology disclosed publiclyDetailed MQ/Wave criteria provided
Perception by PractitionersInspirational and innovation-orientedAnalytical, risk-focused, and conservative
Bias RiskMedium – selection based on innovation appealLow to medium – bias debated but generally rigorous

ProcureTech 100’s primary role was ecosystem-building and digital innovation promotion, not third-party critical evaluation. In short, Lance’s company was a curator and promoter of technology, and in that light, maybe we should cut him a little slack regarding his Rah Rah comment in November.

That said, based on my many years of experience in and covering the high-tech and procurement industries, the above table assessment makes distinguishing between ProcureTech 100 and, say, Gartner’s expressed focus somewhat blurred, bordering on opaque.

The underlying question, which is most important for breaking the generational cycle of ProcureTech implementation failures, is establishing a clear-cut, definable separation of the roles between solution providers (sales & marketing) and the unbiased assessment of industry experts and analysts.

By the way, one should not assume that asking the tough questions about ProcureTech’s effectiveness demonstrates a lack of enthusiasm or belief in the possibilities of what AI can achieve in our industry. I personally love technology. However, that doesn’t mean closing my eyes to practitioner organizations’ challenges in realizing that promise.

The above being said, here is what the clearly defined roles of sales & marketing and independent expert and analyst focus should be:

AspectProcureTech Solution ProvidersIndustry Experts & Analysts
Job ImpactDownplayed; focus on augmentationExplicit concern about displacement
Ethics & BiasRarely addressed in depthCentral concern; call for governance
SecurityNot a primary focus in public commentaryHighlighted as a major risk
Data QualityStressed as operational prerequisiteFramed as a critical risk for bias/errors
TransparencyLimited discussionUrged as essential for trust and safety
Vendor Lock-InNot discussedSeen as a real risk with proprietary tools
Overall ToneOptimistic, benefit-drivenBalanced, sometimes cautionary

Assessment Of The Above Roles

  • ProcureTech solution providers tend to spotlight Agentic AI’s operational benefits, framing downsides as manageable implementation challenges.
  • In contrast, procurement industry experts and analysts adopt a broader, more critical lens—raising alarms about ethical, workforce, security, and governance risks that providers often understate or omit.
  • This divergence highlights the importance for procurement leaders to look beyond vendor marketing and engage with independent analysis when assessing Agentic AI’s true risks and rewards.

The Big Takeaway: About one-third (34%) of C-suite leaders have openly acknowledged that AI adoption at their organization has been a major disappointment, and 68% say AI adoption has caused division within their company. These figures reflect more frustration with implementation challenges and internal alignment than fundamental skepticism about AI’s value.

Over the years, I have often stressed that the ProcureTech initiative failure rate has little to do with the technology. In fact, the technology and its promise are incredible, as demonstrated by my DND case study.

From my perspective, the initiative failure rate is due to misaligned marketing, sales overpromising, and ultimately pushing products rather than actually solving problems. These three missteps are the one constant that has run through four to five decades of high implementation failure, and these failures will continue until we start using an Agent-based development and implementation model.

BONUS TABLE ON LEVEL OF SKEPTICISM

MODEL 1

GroupSkeptical (%)Top Risks Cited
Industry Experts/Analysts~37%Bias, transparency, job loss, privacy, security, ethics, regulatory gaps
Business Leaders (general)<40%Data breaches, inaccurate outputs, legal liability, ROI, organizational disruption
Insurance Agency Principals27%Data privacy, lack of trust, business disruption
Compliance ProfessionalsRisingEffectiveness doubts, governance, data quality
ProcureTech Solution Providers25–40% (indirect)*Short-termism, misaligned implementations, trust erosion, market failure, FOMO-driven risk
GartnerHigh (30%+ projects abandoned)Project failure, poor data quality, risk controls, cost overruns, unclear value, hype-cycle disappointment
McKinsey47% say AI too slow; only 1% matureTalent gaps, slow ROI, lack of maturity, workforce planning, ethical oversight, trust gap
Deloitte77% “concerned to a large extent”Regulatory compliance, cybersecurity, data provenance, infrastructure, hallucinations, governance
Procurement Leaders (AI impact)Only 35% see high impactData privacy, integration, accuracy, ROI uncertainty, governance
Sourcing Industry Group (SIG)Moderate to highSpeed of change, lack of creator control, job displacement, bias, ethical use, explainability, transparency1
Procurement FoundryModerateData quality, integration, change resistance, impact on expertise, trust in outputs2
Institute for Supply Management (ISM)Moderate to highData privacy, job displacement, bias/fairness, transparency, overreliance, ethical sourcing, human oversight3
National Institute of Governmental Purchasing (NIGP)Moderate to highBias, cybersecurity, change resistance, cost/resource constraints, ethical concerns4
Chartered Institute of Procurement and Supply (CIPS)Moderate to highMisinformation, bias, explainability, privacy, accountability, security, continual assessment5

*ProcureTech solution provider skepticism is inferred from market pressures and failure rates rather than direct survey data.

MODEL 2

Source/OrganizationPercentage SkepticalRisks Associated with AI
Pew Research Center (2024)55% of AI experts– Lack of trust in responsible AI development (biased algorithms, misuse in hiring/healthcare). – Insufficient regulation (57% demand stronger oversight). – Existential threats (equated to pandemics/nuclear war).
YouGov (March 2025)44% of professionals (47% societal concerns)– Societal impact (misinformation, deepfakes, 30% reputational risk). – Job displacement (28% fear role reduction). – Ethical concerns (discrimination, biases).
Salesforce (2024)40% of non-users, 54% distrust data– Lack of familiarity (40%), distrust in training data (54%). – Poor outcomes (56% struggle with results). – Integration challenges with existing systems.
KPMG (2023)61% ambivalent/unwilling to trust– Ethical misuse (bias, accountability issues). – Lack of expertise (implementation errors). – Regulatory compliance risks.
Insurance Portal (2025)30% lack expertise, 30% ethical concerns– Lack of expertise (30%), ethical use (30%), compliance issues (27%). – Data reliability risks affecting outcomes.
Takepoint Research (2024)20% of cybersecurity professionals– Overreliance and manipulation risks. – Cybersecurity threats (AI-driven malware). – Integration difficulties (68%).
Elon University (2025)23% predict negative outcomes– Degradation of human capabilities (empathy, critical thinking). – Societal risks (misinformation, economic disruption). – Existential concerns (AI outsmarting humans).
Gartner~40–50% (inferred from cautious adoption insights)– Data quality and governance issues (incomplete datasets, bias). – High implementation costs and complexity. – Security risks (AI-driven cyberattacks, vulnerabilities).
McKinsey~30–40% (inferred from risk-focused reports)– Job displacement and workforce reskilling needs (30–40% of tasks automatable). – Ethical and bias risks (algorithmic fairness). – Regulatory uncertainty slowing adoption.
Deloitte~50% (inferred from trust and risk surveys)– Lack of trust in AI outputs (data quality, bias). – Cybersecurity and privacy risks (data breaches). – High costs and expertise gaps delaying ROI.
Sourcing Industry Group (SIG)~30–40% (inferred from procurement caution)– Integration challenges with legacy systems. – Ethical concerns (bias in supplier selection). – Data security risks in procurement processes.
Procurement Foundry~30% (inferred from community discussions)– Lack of expertise in AI procurement tools. – Cost unpredictability in AI adoption. – Concerns about vendor lock-in and scalability.
Institute for Supply Management (ISM)~35–45% (inferred from supply chain caution)– Supply chain disruptions from AI errors (data quality). – Ethical risks in automated decision-making. – Regulatory compliance challenges.
National Institute of Governmental Purchasing (NIGP)~40% (inferred from public sector caution)– Ethical and transparency issues in public procurement. – Data privacy and cybersecurity risks. – Limited expertise in government AI adoption.
Chartered Institute of Procurement and Supply (CIPS)~35–40% (inferred from ethical focus)– Ethical risks (bias, accountability in procurement). – Data governance and quality concerns. – High costs and training needs for AI tools.

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Posted in: Commentary