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Tag: Product Strategy

From Workflows to Intent: How AI Agents Are Reshaping Procurement Tech

Posted on by Constantine Limberakis

Over the past year, many of the most substantive conversations I’ve had with CPOs, CIOs, and leaders at start-ups and growth-stage technology companies have revolved around a common, often unstated question: What happens to enterprise software when users no longer interact with it the way it was designed to be used?

For procurement leaders, this question surfaces around control, trust, and accountability.
For technology providers, particularly those building and scaling solutions, it surfaces around differentiation, relevance, and long-term value creation.

That convergence is why I view AI agents as one of the most consequential trends in enterprise B2B technology today. Not because of the novelty of large language models, but because of what they represent: a structural shift in how intent, data, and decision-making come together. For procurement and supply chain leaders, this shift is no longer theoretical. For technology providers, it is becoming a defining strategic test.

A Lesson From an Earlier Inflection Point

Early in my career, I remember working with Ariba Operating Resource Management System (ORMS) – (yes this is what it was called 😀 ) at a time when workflow was emerging as a true competitive differentiator. What set it apart was not simply functionality, but visibility. The workflow designer made approval paths tangible — POs, requisitions and any electronic or Eform could be modeled, demonstrated, and understood visually in term of approval state.

At the time, this was a sharp contrast to solutions like SAP SRM, which often struggled to show even basic approval processes in a way business users could clearly grasp. That lack of visibility mattered. Buyers hesitated when they could not see how work actually moved through the system. This workflow visibility combined with reporting became a game changer. It shifted buying decisions because it reduced ambiguity and increased trust. Users did not just assume the system worked—they could see how it worked.

That moment is worth remembering, because the pattern is repeating.

Why This Moment Matters

Enterprise software has historically evolved by layering on more capability — more workflows, more configuration, more dashboards. When adoption lagged, the response was better UI/UX, better design and not a fundamental rethink of interaction of humans and computers.

Generative AI and AI agents change that equation. Instead of learning systems, users increasingly express intent: Where am I exposed to supplier risk? What should I renegotiate next? How do I protect margin without disrupting supply?

What makes this shift unavoidable is convergence. Mature LLMs, accessible agent frameworks, enterprise-grade security tooling, and years of accumulated structured and unstructured data have all matured at the same time. The result is a new interaction model that feels as significant as the move from command lines to graphical interfaces—and arguably more disruptive.

From User Experience To Outcome Experience

Traditional procurement platforms were designed around processes. Users navigated workflows, followed steps, and consumed outputs through reports and dashboards.

Agent-driven interaction reverses that logic. The user starts with the outcome. The agent interprets intent, reasons across structured and unstructured data, invokes workflows across systems, and returns a recommendation—or executes it.

For CPOs, this lowers friction but raises stakes. Decisions happen faster, but they also risk becoming opaque if not governed correctly. Just as workflow visibility once built trust, explainability will now define it.

Four Questions Every CPO Should Be Asking Now

As this shift accelerates, CPOs should anchor their technology strategy around four critical questions:

1. Where does decision authority sit—human or agent?
 As agents recommend suppliers, flag risks, or trigger actions, CPOs must define where automation is acceptable and where human oversight is mandatory. This is not a configuration issue; it is a governance decision.

2. Can the system explain its recommendations in business terms?
 Trust will determine adoption. If an agent cannot clearly articulate why a recommendation was made—what data it used, what assumptions it applied, and what trade-offs it considered—CPOs will hesitate to rely on it for material decisions.

3. How effectively does the platform reason across fragmented data?
 Procurement decisions increasingly depend on unstructured inputs—contracts, supplier communications, market intelligence, ESG disclosures. Platforms optimized only for structured ERP or S2P Suite data will struggle as agents become the primary interface.

4. What happens to the procurement operating model?
 As agents automate analysis and execution, procurement roles shift toward exception management, supplier strategy, and value orchestration. Skills, roles, and accountability models must evolve accordingly.

What This Shift Means For Technology Providers

The Ariba ORMS example is instructive for today’s technology providers. At that time, workflow visibility—not just workflow capability—became the differentiator. Today, AI agents face a similar test. The foundational components of agent-based systems are rapidly commoditizing. LLMs, orchestration frameworks, vector databases, and enterprise AI tooling are broadly accessible.

Differentiation will not come from having an agent, but from what sits beneath it:

  • Embedded domain intelligence, not generic automation
  • Decision governance and explainability, not black-box outputs
  • Outcome reliability, not surface-level AI features

Providers that cannot clearly show how decisions are made will face the same skepticism once directed at opaque workflow engines.

Suites Vs. Best of Breed in an Agent-Driven World

The long-standing suite versus best-of-breed debate does not disappear — it evolves.

Suites benefit from unified data models and end-to-end process visibility, enabling agents to reason across sourcing, contracting, planning, and execution. This supports broader orchestration but may dilute depth.

Best-of-breed solutions retain an advantage in specialization and analytical rigor. However, without a compelling agent narrative, they risk becoming invisible components under a higher-level orchestration layer.

For CPOs, the right question is no longer “Which solution is better?” It’s “Which ecosystem enables agents to deliver trusted, explainable outcomes across the wider source to pay value chain?“

Will The Prompt Be the Differentiator?

Prompts and prompt design will become the dominant interaction surface—but they will not be the competitive advantage.

Two platforms can receive the same prompt and deliver very different outcomes based on data architecture, reasoning logic, governance rules, and embedded expertise. So as interfaces fade, decision quality becomes the new battleground.

  • For CPOs, the mandate is clear: demand transparency, accountability, and control.
  • For technology providers, the challenge is sharper: prove that your platform still matters when the screen no longer does.

The interface may disappear. Strategic relevance cannot.

How Liberis Consulting Helps Navigate This Shift

For start-ups and growth-stage technology providers, the move toward agent-based interaction creates both opportunity and confusion. The market is crowded with vendors leveraging similar AI tooling, making differentiation increasingly difficult. Liberis Consulting works with technology companies that recognize this moment as a strategic inflection point. We help providers:

  • Define where intelligence truly lives within their platform
  • Design agent strategies that prioritize explainability, trust, and control
  • Align product direction with how CPOs evaluate value and risk
  • Position effectively against suites and adjacent competitors
  • Translate technical capability into clear, credible market narratives

Just as workflow once separated leaders from laggards, agent intelligence will now determine who shapes the next generation of procurement technology. Liberis Consulting helps ensure your platform is on the right side of that divide.

 Learn more at  Liberis Consulting.



Procurement’s Next Shadow Problem: DIY AI is the New Excel

Posted on by Bill DeMartino

For decades, MS Excel has quietly powered the procurement function in many capacities, both upstream and downstream. It’s flexible, familiar, and—critically—under user control. Even after multiple waves of enterprise tech, teams still default to spreadsheets and email because most systems feel too slow, rigid, or disconnected from how procurement really works.

Now, a new force is accelerating that same do-it-yourself mindset: generative and agentic AI. With tools like OpenAI’s ChatGPT, Anthropic’s Claude, and Google Gemini, procurement professionals can spin up RFP drafts, generate supplier scorecards, summarize market research, or even build mini decision engines—instantly. The friction is gone. The result? A surge in homegrown solutions that look a lot like the Excel shadow systems of the past—but move faster, proliferate wider, and carry even more risk.

Why This Is Familiar—yet Different

AI is unlocking exactly what Excel once offered: speed, autonomy, and flexibility. Need to build a new supplier intake workflow? An AI tool can mock up the first version. Want to summarize contract terms? A prompt can extract key clauses. What’s different now is personalized access to AI at a new level of personalized scale. This next generation of AI in the form of generative and agentic tools make it far easier for every team member, not just the Excel superusers, to create bespoke workflows in minutes.
In the short term, this looks like progress. Teams seem more productive. Ideas get tested more quickly. Processes feel more responsive. But beneath the surface, the same old cracks are starting to show.

Silos, Misinformation, and the Loss of Control

Just like Excel once created pockets of hidden data, these next gen AI tools can quickly fracture the procurement landscape. Prompt outputs live on desktops or in chat windows. Decisions are influenced by models no one can audit. Processes evolve in parallel without coordination. There’s no common language, no shared data foundation, no traceability.

This isn’t just a governance problem. It’s a performance problem. When sourcing decisions are based on local models or potentially hallucinated insights, the organization starts making the wrong bets. And because no one sees the full picture, the errors compound.

The Real Risk Isn’t Security. It’s Suboptimal Procurement

Yes, shadow AI poses security concerns. But those will be addressed—through enterprise controls, policy frameworks, and better tooling. The deeper risk is strategic misalignment. If every team builds their own agentic assistant to handle sourcing, intake, or supplier scoring—without shared logic or data—they’re solving today’s pain at the cost of tomorrow’s cohesion.

Left unchecked, this trajectory leads to an even messier version of the Excel era: fragmented decision logic, duplicated tools, disconnected insights. Procurement gets faster, but not smarter or more efficient.

There’s a Better Path: Reinvent the Operating Model

Generative and agentic AI are not just a faster Excel. It’s a chance to redesign how procurement operates. That means shifting from DIY experimentation toward intentional architecture. From individual agents to coordinated intelligence. From workaround tooling to strategic capabilities.

And that doesn’t mean reverting to rigid systems. A new class of tools is emerging—native AI platforms designed for procurement. These blend generative and agentic capabilities to support tasks like always on intelligence, autonomous sourcing, intelligent Intake and Orchestration (I&O), and dynamic supplier engagement. These aren’t generic copilots—they’re purpose-built systems that can learn, adapt, and connect across the procurement lifecycle.

The opportunity is to move beyond task-level acceleration toward true workflow reinvention. To harness AI not just to replicate the old ways faster, but to architect smarter, more transparent, and value-aligned processes from the ground up.

It starts with a clear mandate: channel the creativity next gen AI enables into a shared system of value. Build an AI operating layer that’s governed, data-rich, and procurement-specific. Let teams create—but on rails. Make it easy to innovate without going rogue.

Done right, next gen AI won’t just automate current workflows. It will change what’s possible. And procurement won’t just survive the next shadow wave—it’ll lead it.

At Liberis we work with startups and growth-stage procurement and supply chain solution providers to clarify and amplify their voice so they can stand out, resonate with enterprise buyers, and scale effectively.

👉 Learn more at Liberis Consulting.

After the Lights Fade: Reflections from DPW Amsterdam 2025

Posted on by Constantine Limberakis

Before the buzz of DPW Amsterdam began, I had the privilege of spending a quiet day ahead of the conference at the Rijksmuseum—standing before masterpieces that have endured for centuries. Works by Rembrandt, Vermeer, and Hals—each brushstroke preserved through wars, revolutions, and generations—remind us that true craftsmanship withstands the tests of time.

It was a striking contrast to what awaited later that week: the fast-moving, high-decibel world of procurement and supply chain technology, where innovation cycles turn in months and yesterday’s breakthrough can quickly become tomorrow’s memory. At the Rijksmuseum, permanence is celebrated; at DPW, impermanence is reality. The question that lingered as I left the museum was the same one that echoed through the conference halls: what in this rapidly shifting landscape will truly endure—and what will fade just as quickly as it arrived?

Another DPW Amsterdam has come and gone. The music, lights, and unmistakable energy of the world’s most forward-leaning procurement and supply chain conference still echo a week later—but so do the questions. Beneath the spectacle lies a deeper conversation about what’s next: which technologies, companies, and ideas will truly shape the year ahead—and which might quietly fade before we meet again next fall.

This year’s event was bigger, louder, and more crowded with vendors than ever before. The exhibition floor reflected the growing gravitational pull of procurement and supply chain tech as a magnet for innovation. Yet amid the booth activations and slick demos, what stood out most was the rise of start-ups—scrappy, ambitious teams determined to define the next wave of digital transformation. They represent the foundation of future innovation but also its inherent volatility.

Practical Founders (2025) estimated that for every 100 software or SaaS startups, roughly 10% advance past each meaningful growth stage, suggesting that only about 1 in 10 ever reach sustainable revenue or multi-year viability. That sobering reality hung in the air as founders pitched, networked, and hustled to make an impression in a crowded market.

Adding to the complexity, the majority of startups at DPW were European—many of whom operate in a funding environment that is fundamentally different from the U.S. landscape. According to Forbes, less than 1% of small businesses in the United States receive funding from venture capital firms, while roughly 26% of European startup founders rely on VC backing. That dependency shapes both the optimism and the urgency felt at events like DPW, where visibility, investor access, and early traction can make or break a company’s runway.


Hype Meets Reality

The questions being asked at DPW were not new—but they carried a sharper edge this year.

When does hype become reality? Which vendors will still be here next year? And how many will quietly disappear—whether through cost-cutting, acquisition, or the simple math of survival in an over-invested market?

The AI narrative, unsurprisingly, dominated discussions. GenAI and the emerging concept of Agentic AI were front and center, but so were the anxieties they’ve unleashed. Everyone—from procurement leaders to startup founders—seemed to be asking the same thing: How do I adopt AI without overreaching? How do I move fast enough to stay competitive, but not so fast that I trip over my own ambition?

This tension—between speed and readiness—was everywhere. Many attendees are still in early pilot stages, experimenting with generative insights, contract summarization, and predictive decisioning. But scaling those capabilities into enterprise-grade reliability remains an unsolved puzzle. The mood, while positive, was not euphoric—it was cautiously optimistic. The crowd seemed more grounded, more focused on execution than excitement.

Standing Out in a Sea of Start-Ups

For the startups exhibiting, another question loomed large: How do you get noticed? With dozens of new vendors competing for the same thirty seconds of attention, differentiation has never been harder. A well-designed booth, clever tagline, or flashy AI integration isn’t enough. Buyers, analysts, and investors are looking for something deeper—proof, not promise.

Standing out now means showing evidence of traction, customer references, and credible results. It means having a clear story about where your product fits, not just in a category, but in the day-to-day of procurement and supply chain professionals. The vendors who manage to communicate that clarity—who demonstrate trustworthiness and commercial readiness—will be the ones still standing when the noise dies down.

Looking Toward 2026

As we head toward the close of Q4 2025, the big question remains: what will DPW 2026 look like?
Who will still be there—and who will not? Some of this attrition will be natural—acquisitions, pivots, market corrections—but some will reflect the deeper truth of our industry: that even great technology is no guarantee of survival.

The next year will likely bring consolidation, sharper messaging, and a renewed focus on ROI. But it will also bring opportunities for those who can bridge the gap between AI potential and practical impact. The ones who balance ambition with readiness—who engage the market early but execute with discipline—will emerge stronger.

Key Takeaways from the Startup Genome Project

If DPW is any indication, 2025 will continue to test how resilient these emerging firms truly are. The Startup Genome Project offers several insights that resonate deeply with what was on display in Amsterdam:

  • Validation takes longer than expected. Early-stage startups need to spend up to 3x longer validating their target markets than founders anticipate—one of the main reasons cash flow and focus are so critical in the first 18 months.
  • Ideas are often overvalued. Founders tend to overestimate the worth of their intellectual property by up to 255%, highlighting the gap between vision and market reality.
  • Pivoting can be a strength. Startups that pivot once or twice during early growth can see 3.6x faster user growth and 2.5x higher returns than those that don’t pivot—or pivot too often.
  • Survival improves with stage. Generally, the failure rate decreases with each round of funding, underscoring why deliberate market engagement and credible traction matter more than speed alone.

These findings echo a common truth seen across DPW: success rarely comes from technology alone—it comes from focus, clarity, and adaptability.

That’s also where Liberis Consulting helps startups chart a sustainable path forward. By guiding early-stage B2B technology providers in defining their market position, sharpening their go-to-market strategy, and engaging analysts and investors with credibility, Liberis helps founders reduce the guesswork between product promise and market proof. In a world where hype cycles move faster than business models, disciplined positioning and execution are the new differentiators.

Just as the art in the Rijksmuseum endures because it was built with intent, depth, and mastery, the technologies that will last in procurement and supply chain will be those grounded in purpose and precision—not just noise and novelty.

For now, the glitz of Amsterdam has given way to the grind of Q4. The questions asked on the DPW stage will be answered not by next year’s buzzwords, but by how companies act in the coming months—how they prioritize, execute, and deliver real value when the spotlights turn off.

About the Author:
Constantine Limberakis is the Founder of Liberis Consulting LLC, a boutique consultancy focused on helping B2B technology providers in procurement and supply chain define market strategy, sharpen positioning, and accelerate growth.

From Hype to Trust: Winning the Positioning Battle for Agentic AI in Procurement

Posted on by 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 atLiberis Consulting.

The Impact of Compressed Adoption Cycles on Product Strategy: Agentic AI in Procurement

Posted on by Bill DeMartino

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.

Niche Down to Stand Out: The Case for Focused GTM Strategies

Posted on by Constantine Limberakis

We all have the same thought—the bigger the market, the bigger the opportunity.  But that just isn’t rooted in what modern marketing has taught us over the last couple of decades:   

  • Your messaging gets watered down. If you’re targeting manufacturers, law firms, and eCommerce brands, you can’t speak directly to any of them.
  • Your website becomes one giant dumpster of word garbage and marketing babble. 
  • Your sales cycles get longer—more personas = more objections. More objections mean more concessions and customization, which means slower deals.
  • Because you sound like everyone else (hello commoditization), price is the only lever you can pull to win a deal. 

Example: Imagine a B2B software product enabling sales teams to generate quotes (e.g., a CPQ solution) quickly.  “CPQ for Any Business” is not very specific – it blends in and will most likely put you in direct competition with some of the most prominent players in the category. If it says “CPQ Platform Built for Sales Teams Selling High-End Manufacturing Equipment,” it immediately stands out to a niche audience that needs that specificity.

The Power of Verticalization: Why Industry-Specific SaaS Wins

Instead of going broad, go deep. Vertical SaaS companies (those that build solutions specifically for one industry) often outperform their horizontal counterparts:

  • This is evidenced in higher sales efficiency. At the $200 million revenue mark, Vertical SaaS firms typically spend $40 million on Sales and Marketing, whereas Horizontal SaaS companies spend nearly $60 million.  (reference:  https://flgpartners.com/saas-industry-centric-business-models-horizontal-vertical/)
  • Investor Confidence: Venture capital interest in vertical SaaS companies has surged, with a notable increase in funding and IPO activity. This trend signifies strong investor confidence in the scalability and profitability of industry-specific SaaS solutions.  (reference:  https://coredevsltd.com/articles/top-vertical-saas-companies/)
  • Higher Valuation Multiples: Public Vertical SaaS companies trade nearly double the Enterprise Value (EV) to Gross Profit multiples of their horizontal peers—11x compared to 5x, respectively. This premium reflects investor confidence in the specialized, defensible market positions that Vertical SaaS companies often occupy. (reference:  https://insights.euclid.vc/p/the-vertical-saas-profit-premium)

Why industry-specific over horizontal?

  • Trust:  Customers trust you more. If your product is built for them, they don’t have to guess whether it will suit their needs.  While you still need to prove it with referenceable clients, the clients you can reference will be relevant.
  • Fewer Objections/Shorter Sales Cycle:  Industry-specific use cases and integrations mean less convincing, fewer objections, and faster onboarding.
  • Messaging Resonance:  Messaging becomes sharper because you can speak your audience’s language better.  For the Government, instead of “customer,” you say “constituent.”

Micro-Niching: When Verticalization Isn’t Enough

You can go deeper even within an industry. That’s where micro-niching comes in—honing in on a specific segment of an industry or role.

Examples:

MehBetterBest
Marketing AutomationMarketing Automation for B2B SaaSMarketing Automation for B2B SaaS Sales Teams
ATS SoftwareATS Software.Marketing Automation for B2B SaaS.ATS Software for Remote-First Tech Startups
Customer Support SaaSCustomer Support SaaS for Financial ServicesCustomer Support SaaS for Wealth Management Firms

Example: Vetcove is an eCommerce platform specifically for veterinary clinics to order supplies. It is not competing with Amazon—it is dominating its niche by focusing wickedly on its audience.

In Warren Buffet’s famous words, “How do you beat Bobby Fischer? Play him at anything but chess.” 

How to Execute a Niche-Focused GTM Strategy

This is where the fun begins. You’ve identified a niche category you believe you can dominate. The next step is integrating it into your go-to-market strategy. But how?  

Nail Your Messaging & Positioning

At Liberis Consulting, every consulting engagement begins with a thorough review of your position.  That is the foundation that defines your go-to market. You must clearly understand who (or what) you compete with today and map it against your capabilities that no other competitive alternative can claim.  This points you to the audience that values the unique value only you can deliver, which helps you understand the market category in which you compete (and are winning).  

Understanding and aligning your positioning enables you to jump into your messaging. It becomes clear who you serve and why you’re different. You can use specific terminology relevant to your audience and connect to the pain points your audience faces.

Ditching broad claims like “we help businesses save time” and replacing them with specifics like “we reduce manual claims processing by 40% for large insurance agencies.”

Pro tip: If your messaging doesn’t match what your customers are talking about, you’re still being too broad.

Develop a Point of View

Once you have a niche down, you don’t stop at your positioning and messaging—you need to own a perspective on the market in which you compete. In a crowded market (particularly in B2B SaaS), having a strong, differentiated point of view (POV) helps establish credibility, attract the right customers, and drive demand beyond just features and pricing.

And that point of view manifests in the content and thought leadership you develop.  In how you pitch to your audience.  How you engage with analysts.  In the stories of your customers, you tell.  All of this should be in your point of view on the problem space.

For Sales-Led GTM Motions, Tailor Your Sales Strategy

You need to teach out your positioning and point of view about your company and your product.  They need to understand your niche inside and out.  

What does that mean?

  • Creating ICP (Ideal Customer Profile) templates that focus on your niche.
  • Training reps to handle niche-specific objections.
  • Training reps on how to pitch value and problem versus features and price.
  • Arming sales with industry-specific battle cards, decks, and customer examples.

Align Your Product Strategy with Your Niche?

This doesn’t matter if your product vision and roadmap aren’t aligned with the audience you’re focused on. However, once you align your product strategy with your niche, prioritizing feature requests that cater to your audience becomes much more manageable. This gives the product team a defensible position and justification over their build priorities; otherwise, it always defaults to the HiPPO (Highest Paid Person’s Opinion).

Final Thoughts

Focusing on a specific audience can be scary and often challenging. But it’s not about exclusion—it’s about focus. It’s about carving out a little space in your audience’s brains that makes you stand out.  

By niching down, you:

  • Avoid direct competition with more established players.
  • Create a stronger value proposition that resonates more deeply.
  • Shorten your sales cycle by reducing buyer hesitation.
  • Build a more defensible position in the market.

Before expanding your reach, ask yourself: Do we need more leads or more of the right leads? Discover the answer and optimize your strategy with Liberis Consulting. Visit us today to learn more.