Author: Bill DeMartino

The procurement technology market is heating up with agentic AI solutions. New vendors appear almost weekly, racing to stake a claim. The result is a crowded landscape where the sheer number of entrants makes it harder than ever for buyers to separate substance from noise.

At Liberis, we’ve been exploring these dynamics from multiple angles. In The Impact of Compressed Adoption Cycles on Product Strategy, we showed how faster adoption curves force product teams to mature capabilities sooner. And in Beyond Buzzwords: Why AI Startups Should Focus on Outcomes, Not Labels, we highlighted the dangers of leaning on terminology instead of delivering outcomes.

This blog builds on both. The sheer volume of new entrants validates the urgency of these themes: buyers need clarity, vendors need sharper positioning, and the market needs guidance on how to cut through the noise. Even when startups move past buzzwords, most positioning still fails to connect with what enterprise buyers actually worry about.

Positioning defines how your solution should be understood in the market. It sets the frame of reference, establishes credibility, and explains why you matter compared to alternatives. Messaging is the articulation of that positioning — how you communicate your solution’s value to buyers, turning the foundation into tailored proof points, narratives, and stories that resonate with specific audiences.

In fast-moving categories like agentic AI, standing out isn’t about who can promise the most features. It’s about who can speak credibly to the buyer’s anxieties — and prove they can overcome them.

The Compressed Adoption Curve

Technology adoption used to be predictable: bleeding-edge innovators, then cautious early adopters, followed years later by the mainstream. Not anymore.

With agentic AI, hype cycles are louder, analyst coverage is faster, and organizational pressure to act is intense. Enterprises aren’t content to “wait and see.” Boards and executives expect procurement leaders to explore AI opportunities immediately, compressing what was once a multi-year curve into a matter of months. That shift means mainstream buyers are arriving earlier, bringing expectations that used to show up much later in a category’s maturity curve. Enterprise-grade requirements around integration, governance, support, and adoption are no longer “future problems” — they’re immediate. Weaknesses that early adopters might have forgiven are now exposed quickly, and credibility is tested from day one.

Four Buyer Anxieties (and Positioning Opportunities)

In product strategy, these anxieties demand new capabilities. In positioning, they demand new language — because as mainstream buyers show up earlier, these concerns surface faster. It’s not enough to claim you’ve solved them. You have to prove it  with credible evidence buyers can trust.

1. Time-to-Value: Deployment & Integration
   
   Buyer fear: “This will take forever, break our S2P system, and ROI will slip away.”
   
   Market signals: Analysts cite fragmented data, ERP/S2P complexity, and the burden of “yet another tool” as top barriers. Buyers know speed and ERP-friendliness are non-negotiable.
   
   Positioning opportunity: Show you can plug into ERP and S2P workflows, supplier networks, and adjacent systems without disruption. Credible positioning highlights rapid integration, workflow fit, and speed to results.
   
   
2. Black-box/Abandonment: Support & Success Model
   
   Buyer fear: “Once it’s live, we’re on our own. Who co-owns outcomes when things go sideways?”
   
   Market signals: Procurement leaders link AI adoption to talent, skills, and operating-model support. Without ongoing help, even promising AI agents risk being abandoned.
   
   Positioning opportunity: Frame AI not as a black box but as a co-pilot model: transparent support, human oversight, success frameworks, and service commitments.
   
   
3. Governance/Obsolescence: Keeping Agents Current
   
   Buyer fear: “Will these agents keep up with policy, compliance, and supplier changes — or go stale and risky?”
   
   Market signals: Oversight, closed-loop learning, and guardrails are now seen as essential. Buyers worry about governance as much as functionality.
   
   Positioning opportunity: Position governance and adaptability as differentiators. Highlight safeguards, auditability, and adaptability as part of the solution’s DNA — not afterthoughts.
   
   
4. Team Trust/Adoption: Community, Training & Adoption
   
   Buyer fear: “My team won’t adopt it. We lack the skills and trust.”
   
   Market signals: Analyst studies show AI adoption depends less on technology itself and more on execution, change management, and peer trust.
   
   Positioning opportunity: Demonstrate investment in enablement, training, and peer communities. Buyers trust solutions with clear adoption pathways.

Positioning Traps to Avoid

Even strong providers stumble when they ignore buyer realities. Four traps come up repeatedly in the agentic AI market:

1. Empty Superlatives
   Claims like “the world’s leading” or “the first autonomous AI agent” may grab attention but rarely build trust. Enterprise buyers expect proof — case studies, analyst validation, adoption data — not puffery. In compressed adoption cycles, credibility > bravado. Unsupported claims risk turning off sophisticated buyers before the sales conversation even begins.
   
   
2. Feature-First Messaging
   Many vendors lead with “we automate sourcing with AI” but stop there. This leaves the “so what?” unanswered — it doesn’t connect to enterprise anxieties like ERP integration, supplier adoption, or governance. Features without context quickly get lost in the noise. What matters is how you prove those features reduce risk and deliver outcomes in the buyer’s environment.
   
   
3. Analyst Echo-Chamber
   Repeating Gartner or Forrester phrases without anchoring them in customer voice comes across as derivative. Buyers notice when language is borrowed versus grounded in real pain points. Analyst framing can aid credibility, but only when combined with customer proof: adoption stories, community validation, peer evidence.
   
   
4. First-ICP Blindness
   Startups often build positioning around their first customer wins, which usually come from buyers with an early adopter mindset. But they fail to evolve as they sell into larger, more risk-averse enterprises. The result: messaging that resonates with one buyer type but alienates or confuses others. This trap is magnified in compressed adoption cycles. Because mainstream buyers show up earlier, vendors who keep speaking only to early adopters risk being dismissed. These buyers bring enterprise-grade expectations around integration, governance, support, and adoption. Positioning must flex across buyer types — from innovators to enterprise committees — or risk losing relevance with the very audience now driving procurement AI decisions.

Modern B2B buying reinforces these traps. Research shows buyers complete 57–70% of their journey before contacting sales, relying on peer networks, AI search, and user-generated reviews. Analyst influence still matters, but peer validation and customer stories often outweigh it. In this environment, what you can prove carries more weight than what you can claim.

Solution Provider Archetypes: Strengths and Gaps

Across the vendor landscape, positioning challenges vary depending on where providers start from. These are not absolutes, but common patterns in how solution providers show up in the market:

• Established S2P Suites – Strong on governance, compliance, and responsible AI narratives — qualities enterprise buyers trust. But because they are not AI-native, their agentic capabilities often appear as extensions rather than core design. This can make them look slower to innovate and more feature-first in their messaging. Their challenge is to prove agility while keeping credibility.

• Intake & Orchestration Platforms – Agile and strong on integration/UX narratives, they shine in user experience and speed to adoption. Yet they often lack the depth of core S2P functionality or governance assurances expected by enterprise buyers. Their challenge is to build credibility in robustness without losing their agility story.

• Niche AI Specialists – Compelling on speed, efficiency, and ROI, they embody the “AI-native” advantage. But they often underplay anxieties around integration, governance, and adoption at scale. Their challenge is to broaden their story to address enterprise-grade requirements without losing their innovation edge.

The winners won’t be defined by where they start — but by how quickly they close these gaps and credibly speak to buyer fears.

The Path Forward

Standing out in a crowded and increasing rapid markets like agentic AI market isn’t about louder claims or more features. It’s about credible positioning:

• Replace superlatives with proof.

• Shift features into buyer-context outcomes.

• Balance analyst framing with customer stories.

• Broaden messaging to span buyer types.

Those who build positioning around trust, adoption, and governance will separate themselves as leaders — not because they shouted the loudest, but because they proved the buyer’s real fears were solved.

Product strategy creates the foundation; positioning makes that foundation visible, credible, and differentiated. Messaging then carries that positioning into the market, tailored to different buyers and contexts. Together, they determine who scales under compressed adoption cycles — and who stalls.

At Liberis we help growth-stage B2B software companies close this gap. We work with founders and product leaders to sharpen positioning, evolve messaging, and align product strategy to compressed adoption realities — ensuring their solutions resonate with enterprise buyers and stand out in crowded markets.

👉 Learn more at Liberis Consulting.

The Story

Agentic AI is no longer an idea for tomorrow — it’s here today. Solutions already exist across sourcing, supplier management, contract review, intake and orchestration, and post-PO execution. And more are arriving in rapid fire. Each month brings new entrants, new capabilities, and new promises of autonomy.

This flood of solutions coincides with mounting organizational pressure — meaning buyers are evaluating and adopting them far earlier than in past cycles. In past waves of technology, solution providers had the luxury of years to refine products before mainstream buyers arrived. With Agentic AI, that window has collapsed to months. Boards and CFOs are demanding efficiency gains immediately, and procurement leaders are under pressure to “do more with less.” That urgency changes how product strategy must be approached.

The Compressed Adoption Curve

The new wave of AI, including Agentic AI, faces a different kind of adoption cycle — one driven less by technology maturity and more by organizational pressure. Boards and CFOs expect measurable efficiency gains this year, not in three. Procurement leaders are told to “do more with less” and increasingly see AI as the lever. No executive wants to explain why their company is behind peers already piloting these tools.

That pressure has accelerated adoption dramatically, collapsing what once unfolded over years into a matter of months. Bleeding edge, early adopters, and mainstream buyers increasingly overlap, leaving little buffer to refine products gradually.

In past cycles, early adopters might have tolerated rough edges. Today, mainstream buyers are arriving much sooner and expect maturity from the start. Solution providers must be prepared to enter the market earlier than before — with products that not only demonstrate value, but also fit seamlessly into enterprise environments and support long-term scaling.

That acceleration means buyer anxieties around deployment, support, governance, and adoption don’t surface gradually — they converge at once. Providers that don’t design for them up front risk being sidelined before they have a chance to scale.

Four Buyer Anxieties (Opportunities for Product Leadership)

1. Deployment & Integration (time-to-value anxiety)

Fear: “This will take forever, break our ERP or S2P platform, and ROI slips into next year.”

Product reality:
Deployment and integration are two sides of the same coin. Buyers expect rapid deployment — configuration that delivers visible ROI in weeks, not quarters. Long rollouts or heavy customization are immediate red flags. At the same time, integration into ERP, S2P suites, supplier networks, and workflows is no longer optional — it’s the baseline expectation.

But integration does not mean blindly automating every existing process. Many enterprise workflows are overly complex or outdated. Simply wiring AI into them risks enshrining inefficiency. The real opportunity is to deploy fast, integrate seamlessly, and reimagine where AI can collapse steps, simplify approvals, or streamline supplier interactions.

Takeaway:
Products that prove quick deployment while fitting into core enterprise environments while also challenging outdated workflows give buyers confidence that AI won’t just bolt onto their world, it will make it better.

2. Support & Success Model (black-box anxiety)

Fear: “Once it’s live, we’re on our own — who co-owns outcomes when things go sideways?”

Product reality: Buyers don’t want “fire-and-forget” automation. They expect providers to stand behind outcomes with clear success models. That means: transparent SLAs, structured onboarding, and co-pilot frameworks that reassure customers they won’t be abandoned post-go-live. Analyst research ties AI adoption success directly to robust customer success programs, not just software delivery.

Takeaway: Products that bake in success models — clear ownership of outcomes, proactive monitoring, and transparent SLAs — shift from selling software to delivering sustained value. This builds trust and accelerates adoption.

3. Governance & Adaptability (obsolescence anxiety)

Fear: “Will agents keep up with policy changes, compliance requirements, and supplier dynamics — or become stale and risky?”

Product reality: Regulations, supplier behaviors, and internal policies evolve constantly. Agents that can’t adapt quickly create risk rather than resilience. To build trust, products must go beyond adaptability and make agent decisions auditable and explainable — with clear logs, transparent reasoning, and update pathways. Embedding human-in-the-loop oversight for high-impact decisions ensures accountability while allowing low-risk processes to flow autonomously.

Takeaway: Products that combine adaptability, auditability, explainability, and human accountability transform governance from a blocker into a differentiator. Governance becomes a visible advantage that reassures buyers, accelerates adoption, and sustains long-term trust.

4. Community, Training & Adoption (team trust anxiety)

Fear: “My team won’t adopt it; we lack skills and trust.”

Product reality: Even the best AI products fail if teams don’t use them. Research shows adoption depends less on technical capability and more on execution, skills, and trust-building. Without confidence and training, teams hesitate — slowing ROI and creating resistance to change.

Takeaway: Products that embed training, peer communities, and intuitive adoption pathways create confidence. When users see peers succeeding and feel supported — not replaced — adoption accelerates. This turns AI from a threatening tool into a trusted enabler.

Product Strategy Checklist: Avoid These Pitfalls

Before committing to market, product leaders should test themselves against these questions:

Deployment & Integration

• Have we built for ERP, S2P, and supplier network integration from day one?
• Can we demonstrate fast deployment and time-to-value without breaking existing environments?
• Are we integrating intelligently, not just replicating inefficient workflows?
  

Support & Success Model

• Do we provide a clear co-pilot framework and outcome co-ownership model that reassures buyers we won’t abandon them post go-live?
• Are our SLAs and success models transparent enough to give buyers confidence in long-term support?
• Is our product positioned to deliver outcomes, not just software?
  

Governance & Adaptability

• Have we embedded auditability and explainability so agent actions are visible and accountable?
• Is there a mechanism for continuous adaptation to policy, compliance, and supplier changes?
• Do we enable human oversight for high-impact decisions while allowing low-risk processes to flow autonomously?
  

Community, Training & Adoption

• Do we offer embedded training and peer communities that encourage adoption?
• Have we created trust-building pathways that make teams feel supported, not replaced?
• Can we show clear adoption success stories that prove teams will use — and value — the product?

From Features to Trust: The Real Edge in Crowded Markets

The solution providers who answer “yes” to these questions aren’t just avoiding pitfalls — they are building the complete solutions procurement leaders are urgently looking for. In an era of compressed adoption cycles, solving for these anxieties as part of a holistic product strategy is what will separate those who scale from those who stall.

And that’s where the competitive edge emerges. Features can be copied, but the ability to combine integration, governance, support, and adoption into a trusted solution is what allows a product to truly stand apart from the competition in a crowded market.

Great product strategy isn’t about chasing the next feature. It’s about building solutions that earn trust, drive adoption, and stand apart in crowded markets. At Liberis Consulting, we’ve done this before, and we know how to help growing companies avoid the pitfalls and scale with confidence. Let’s do it together.