From Drought to Drive: How the Most AI-Ready Firms Turn Readiness into Real ROI

In our earlier piece, The AI Value Drought: Rethinking ROI and Outcomes, we argued that the problem with AI isn’t a lack of ambition – it’s a lack of realized value. Many organizations have experimented with pilots, prototypes, and proofs of concept, only to see returns evaporate before they scale.

Cisco’s 2025 AI Readiness Index, surveying more than 8,000 business and IT leaders across 30 markets, now confirms that readiness – not experimentation – is the differentiator between hype and harvest. The study identifies a group of organizations known as “Pacesetters” — roughly 13% of respondents — who are four times more likely to move AI pilots into production and 50% more likely to report measurable value from their AI initiatives.

These findings reinforce a hard truth for GTM and value leaders: AI success is not a function of innovation alone. It’s a function of readiness, alignment, and discipline.

The Rise of the AI Pacesetters: Readiness as a Competitive Advantage

Cisco’s data paints a clear picture. Pacesetters outperform their peers across every key measure of AI value because they treat AI not as an experiment, but as a strategic system.

• 99% have a defined AI roadmap (vs. 58% overall).
  
• 91% have a formal change-management plan (vs. 35%).
  
• 79% prioritize AI as their top investment focus (vs. 24%).
  
• 95% track AI’s business impact — three times higher than others.
  
• 90% report measurable gains in profitability, productivity, and innovation.
  

The takeaway?
Pacesetters design for value before they deploy for value. They invest in the architecture, governance, and measurement systems that turn AI from concept into capability.

For CROs and GTM leaders, this isn’t just an operational lesson — it’s a strategic one. The companies that build AI readiness into their GTM and customer value frameworks will capture market share faster, retain customers longer, and command higher win rates than those still chasing pilots and promises.

Agentic AI: Ambition Outpacing Readiness

Cisco’s report also spotlights the next frontier of enterprise AI — agentic systems that can act autonomously, not just analyze or assist.

• 83% of organizations plan to deploy AI agents.
  
• Nearly 40% expect agents to work alongside employees within a year.
  
• Yet only 15% describe their networks as adaptable or scalable enough to support these systems.

This mismatch between ambition and capability should sound familiar to anyone who’s lived through a digital transformation cycle. It’s what Genius Drive calls the AI Adoption Gap — where technical excitement outruns operational maturity.

Agentic AI has the potential to accelerate decision cycles, automate repetitive workflows, and elevate human roles to higher-value problem solving. But without scalable data, secure networks, and governance frameworks, these “agents” can become costly, opaque liabilities rather than productivity multipliers.

Pacesetters are again the exception. They’ve already laid the groundwork for agentic systems — flexible networks, centralized data, integrated security, and clear ownership models. Their readiness doesn’t just mitigate risk; it amplifies return.

AI Infrastructure Debt: The Silent Drag on Value

Cisco introduces a term every CRO and GTM strategist should internalize – AI Infrastructure Debt.

It’s the accumulation of deferred upgrades, fragmented data, insufficient compute, and underfunded architecture that quietly erodes AI value over time.

The warning signs are already here:

• 62% of organizations expect workloads to rise more than 30% within three years.
  
• 64% struggle to centralize data.
  
• Only 26% have robust GPU capacity.
  
• Fewer than 1 in 3 can detect or prevent AI-specific threats.
  

In financial terms, infrastructure debt behaves like compound interest – the longer it’s ignored, the costlier it becomes to fix.

From a CRO’s perspective, AI Infrastructure Debt translates directly into sales risk – slower deployments, lower adoption, higher churn, and eroded ROI narratives. When buyers can’t operationalize what they’ve purchased, value stories collapse and renewals weaken.

This is why leading GTM organizations are building readiness enablement into their customer lifecycle – helping customers mature their data, infrastructure, and security postures as part of the value journey. It’s not just presales engineering anymore; it’s value engineering.

From Readiness to ROI: Lessons for GTM and Value Leaders

At Genius Drive, we see Cisco’s data as proof that AI value follows readiness, but also that readiness without a value narrative is wasted potential.

Let’s explore the four key lessons for commercial and value leadership teams:

1. Sell the System, Not Just the Solution

Top performers in AI-driven markets don’t sell standalone use cases – they sell ecosystems.

Readiness has become part of the offer. Whether you’re an ISV, SaaS vendor, or value consultant, your GTM story should include how your solution accelerates the customer’s AI maturity. This is how you position as a strategic partner, not a transactional vendor.

2. Quantify Value Like a Pacesetter

Cisco’s research shows that 95% of Pacesetters measure impact rigorously. Yet many GTM teams still rely on anecdotal proof points.

High-performing value leaders are operationalizing quantification – embedding ROI dashboards, time-to-value metrics, and customer outcome benchmarks into every deal.

Quantification builds confidence. Confidence accelerates conversion.

3. Mind the “AI Infrastructure Debt” During Sales and Success

Every buyer carries a different level of readiness debt. Recognizing it early prevents deal friction later.
In pre-sales, assess readiness risk and tailor your proposal accordingly. In customer success, map your adoption strategy to their weakest pillars – data, governance, culture, or talent. This is proactive value management in action.

4. Turn Trust Into Differentiation

Cisco notes that 87% of Pacesetters are highly aware of AI-specific threats, and 75% have security controls built in.

For GTM leaders, this means one thing: trust is the new differentiator.

Every AI conversation must demonstrate control, compliance, and ethical governance. Winning trust wins deals, renewals and growth.

The Readiness → Value Playbook

We believe GTM and value leaders should use a five-stage model to close the gap between AI ambition and realized outcomes.

This readiness-value loop mirrors the behavior of Cisco’s Pacesetters –  continuous investment, continuous measurement, continuous value creation.

Value Leadership in the AI Era

As value and GTM leaders, we stand at an inflection point.

AI’s promise has never been greater –  but neither has the pressure to prove its ROI. Cisco’s research validates what Genius Drive has championed for years: the next wave of winners will be those who sell, deliver, and sustain AI value –  not AI hype.

To do that, we must:

• Equip sellers to tell readiness-based value stories.
  
• Empower customers to assess and close their readiness gaps.
  
• Institutionalize measurement discipline –  from deal stage to renewal.
  
• Build trust and transparency into every engagement.
  

Because when readiness meets value management, the drought ends –  and the drive begins.

The Bottom-Line

The Pacesetters’ advantage is not luck. It’s leadership.

They’ve architected systems that make AI a continuous value engine – not an isolated project.

For CROs, GTM, and value leaders, the question is no longer whether AI delivers ROI.
It’s whether your organization – and your customers – are ready to deliver it repeatedly.

Sources: This article draws from Cisco’s AI Readiness Index 2025 and Genius Drive’s ongoing research on AI value selling, readiness enablement, and the evolution of ROI storytelling in the Outcome Economy.

Lets discuss how to become a value-focused AI Pacesetter today: Click here to schedule a consult with us.