Key Takeaways
- Adoption vs. Transformation: AI is now broadly deployed across enterprises, but impact remains uneven: in recent surveys, a segment of “future-built” firms reports materially higher revenue uplift from AI initiatives, while many peers see limited or no measurable gains.
- The New Moat is Operational: We believe the new foundation for competitive advantage rests on three factors: proprietary data, effective learning loops, and deployment speed.
- Inflection Points Are a Choice: An AI-driven inflection point is a signal, not a crisis. It prompts a deliberate choice between strategic pathways: M&A, a capital raise, or organic growth.
The New Competitive Landscape
The global economy has entered a new structural era — one increasingly defined by the convergence of artificial intelligence, ubiquitous connectivity, and automation: the Intelligent Economy. Together, these forces are influencing how value is created, delivered, and defended across industries.
This transformation is no longer theoretical. Data from Stanford HAI’s “2025 AI Index Report”¹ shows a significant jump in adoption, with 78% of organizations reporting AI use in 2024, up from 55% the prior year.
This adoption data, however, can be misleading. Adoption does not equal transformation. We observe a sharp divergence in outcomes, and this is not a theoretical divide. The stakes of this value gap are high: according to a BCG analysis, firms classified as “future-built” are dramatically outpacing peers, reporting fivefold-higher revenue gains and threefold-greater cost reductions from their AI initiatives.2 This suggests a new landscape of performance.
This gap is reinforced by further data. The same BCG analysis reports that 60% of companies are “stagnating or emerging” on AI maturity,2 while a 2025 McKinsey study finds that even as companies realize “use-case-level cost and revenue benefits,” this innovation is rarely achieved at scale.3
Despite this gap, broader adoption suggests that AI is becoming a foundational utility, much like electricity or cloud computing.⁴ In many sectors, the pace of adaptation is a key differentiator. Firms that learn and act faster tend to defend share — especially where data and model improvements build on each other.⁵
Within this environment, inflection points — moments where strategy, capital, and timing intersect — are increasingly common in many sectors. They can arise when capabilities lag demand, when AI-native competitors redefine value, or when investors and markets prompt clarity about strategic direction and value drivers. Companies that identify and act on these points early may seek to enhance their ability to sustain momentum; outcomes vary by context, and delaying may increase execution risk or opportunity costs.
At the same time, AI introduces a tension in market dynamics. Automation and analytics can expand margins and unlock growth, yet they may also compress pricing power and, in some markets, accelerate consolidation. Our market observation points to a significant shift. We believe markets may increasingly reward companies that demonstrate differentiated data, defensible workflows, and disciplined execution, while posing challenges for generalists and slow adopters. In this context, traditional sources of advantage — such as scale, distribution, and proprietary technology — appear to be less durable amid rapid technological change. For example, AI's competitive impact is not evenly distributed; research from BCG indicates 70% of AI's potential value is concentrated in core business functions, such as R&D, manufacturing, and digital marketing. This allows 'future-built' firms to reshape these specific functions, potentially eroding the broad, pre-existing advantages of incumbents.2
In our analysis, we believe a new foundation for competitive advantage rests on the combination of three compounding factors. These factors, which are informed by research on proprietary data,6 continuous learning loops,7 and deployment speed,6 create a new, more resilient competitive framework.
“We believe a new foundation for competitive advantage is emerging from three compounding factors: proprietary data, effective learning loops, and deployment speed.”
In the Intelligent Economy, organizations that build and apply these capabilities effectively may enhance their capacity to adapt, learn, and compete in markets that reward responsiveness and continuous improvement.
For leaders of lower-mid-market technology and AI-enabled services companies, the implications may be near term. In this environment, we believe a clear plan, a grounded understanding of data assets, and disciplined execution can help teams navigate complex markets. Progress often begins with recognizing potential inflection points and choosing responses aligned with objectives, resources, and risk tolerance. Outcomes vary by company-specific circumstances and market conditions.
In our view, in fast-moving markets, inaction itself represents a strategic choice that may carry significant competitive risk or opportunity cost.
The Diagnostic: Identifying Your AI-Driven Inflection Point
An inflection point is not a crisis; it’s a signal that the current playbook is losing its fit with the market. For leaders in the lower mid-market, the challenge is recognizing this signal before the market forces a reaction.
“An inflection point is not a crisis; it’s a signal that the current playbook is losing its fit with the market.”
How do you know if you are at an inflection point? In our experience, we find that most lower mid-market technology companies and services firms are facing one or more of six common triggers. If these themes resonate, it may be an opportunity for leaders to evaluate strategic priorities.
1. The Capability Gap
Symptom: Client demand is outpacing your AI or data capabilities. RFPs and renewal conversations increasingly require features or automation that your current team and technology cannot deliver.
Key Question: What is the time-to-impact versus the time-to-build — and what premium are you willing to pay for speed?
2. The Growth Plateau
Symptom: After a period of steady growth, expansion flattens. Sales cycles lengthen, and the tactics that previously drove growth are no longer effective.
Key Questions: Is the market consolidating now? Are you positioned to be a future platform, or are you at risk of becoming a feature within someone else’s?
3. The Generational Competitor
Symptom: AI is becoming increasingly efficient, cost-effective, and widely accessible.1 In our observation, AI-native entrants seek to reset unit economics, aiming to undercut incumbents on price while matching or surpassing their performance. For example, DeepSeek competes with OpenAI by undercutting model pricing while narrowing the performance gap.8
Key Question: Where can your business create durable, differentiated value, leveraging your domain expertise and proprietary data in ways a generalist AI model cannot?
4. The "Data-Rich, Insight-Poor" Problem
Symptom: You possess years of valuable, proprietary client and operational data, but it remains locked in systems, un-monetized and unused as a strategic asset.
Key Question: What is the most capital-efficient path to evaluate this data as a potential strategic asset or new revenue stream?
5. The Unsolicited Offer
Symptom: A strategic buyer or private equity firm approaches with an offer. The valuation is often based on your trailing EBITDA but fundamentally discounts the strategic option value of your data, AI roadmap, and market position.
Key Question: How are you currently valuing the strategic option value of your data and AI roadmap, and how does that compare to the market’s perception of your trailing performance?
6. The Founder/Team Bandwidth Limit
Symptom: The company’s growth, or the technical demands of the AI shift, is outpacing the leadership’s capacity. The leadership team is at capacity, and execution or operational scale is beginning to show strain.
Key Question: Does the next stage of growth require a new leadership structure, specialized (and high cost) AI talent, or an operational partner to achieve its full potential?
In our analysis, these six triggers may be viewed as illustrative symptoms of a potential gap in one or more components of the new competitive moat. A “Capability Gap,” for example, could indicate a challenge with “Deployment Speed,” while the “Data-Rich, Insight-Poor” problem might suggest an opportunity to better leverage “Proprietary Data” as a strategic asset.
The Navigation Framework: A Diagnostic for Structuring Strategic Decisions
A Framework for Discussion
The triggers and framework presented here are illustrative. They are intended to help leadership teams frame strategic attention and structure complex discussions. These triggers are not diagnoses, recommendations, or prescriptive guidance; rather, they provide key questions to evaluate the trade-offs inherent in any strategic path. We note that these triggers can interact and may compound; for instance, if capability gaps persist, growth may stall.
The relevance of these concepts varies by company and context. Any decision to pursue a strategy or transaction should be based on a company-specific assessment and made only after consulting with qualified legal, tax, and financial advisors.
The Strategic Framework: Three Pathways
This framework provides a way to think through different approaches rather than a set of prescribed actions — it is useful to note that no option is inherently superior. Each involves potential advantages and material risks, and outcomes depend on factors such as execution, timing, market conditions, and organizational readiness.
The following sections summarize typical considerations observed across mid-market companies navigating similar transitions.
Pathway 1: The Structural Pathway
M&A can be viewed as one potential tool for acquiring capabilities, scale, or market access. In some cases, it enables faster transformation than internal development, though it also introduces integration and cultural complexity.
Common Observations
On the buy-side, companies sometimes acquire niche AI or data-rich peers to address capability gaps or accelerate product development.
On the sell-side, some founders choose to align with larger platforms that can provide broader reach or additional resources.
Key Considerations & Material Risks
While M&A is one pathway companies may use in an attempt to accelerate capability acquisition, it also involves significant integration, cultural, and financial risks. M&A integration carries substantial risk. For example, a 2023 McKinsey survey identified “lack of cultural fit” as a primary reason integrations fail to meet value creation expectations.9 Evaluating transaction structure, post-close retention, and cultural alignment is critical, as outcomes vary widely by execution and market context.9
Leadership Perspective
In modern M&A, a company’s data posture (strategy, quality, provenance) may be considered alongside financial performance and other market factors during discussions and valuation. Depending on timing, cost, and integration considerations, leaders can assess whether partnerships or acquisitions are a practical way to address capability needs relative to building internally.
Pathway 2: The Financial Pathway
External capital can sometimes serve as a catalyst for transformation when the strategic direction is clear but internal resources are limited. The distinction between commodity capital and strategic capital often lies in the value partners bring beyond funding — such as distribution channels, data access, or sector expertise.
Common Observations
Funding rounds are typically anchored to near-term milestones (12–24 months). Data readiness and governance are frequent areas of underinvestment, which can affect scalability and return on new capital.
Key Considerations & Material Risks
Raising capital may enhance flexibility but introduces dilution, governance oversight, and performance expectations from investors. Strategic capital can add alignment and expertise, yet it also invariably alters decision-making dynamics, governance, and founder control. Companies, in consultation with their professional advisors, often evaluate investor suitability, cost of capital, and operational capabilities before proceeding with any capital-raising transaction.
Leadership Perspective
Alignment between investors and leadership can be as important as valuation. Some investors may contribute relationships or industry knowledge, while others may be primarily financial partners. Evaluating these distinctions helps determine whether a capital partnership supports long-term objectives and governance requirements.
Pathway 3: The Organic Pathway
This pathway emphasizes optimizing existing resources — people, data, and relationships — to strengthen the company organically or through alliances while retaining control.
Common Observations
Product Development: Firms may focus R&D on narrow, high-value use cases where proprietary data provides differentiation.
Strategic Focus: Concentrating on a defined vertical can improve specialization and client relevance.
Alliances: Partnerships with larger platforms or technology providers can extend capabilities without requiring ownership changes.
Key Considerations & Material Risks
This pathway also carries the material risk of market obsolescence. While preserving control, a company may be outpaced, out-funded, or out-innovated by competitors who use M&A or external capital to acquire capabilities more rapidly. Outcomes are not guaranteed and depend heavily on execution and competitive response.
Leadership Perspective
In an environment shaped by rapid technological change, companies focusing on specialized markets or capabilities may find clearer differentiation. However, performance varies by industry dynamics, investment discipline, and competitive response.
The Strategic Imperative for Leaders
Inflection points often emerge from technological acceleration. In our observation, decision cycles in the Intelligent Economy can compress and the cost of delay can rise. For lower mid-market leaders, the task is to read these moments clearly and act deliberately within their specific context.
Whether prompted by capability gaps, consolidation, or organizational capacity, inflection points sit at the intersection of strategy, capital, and timing. The framework presented here is intended to structure decision-making and help leaders evaluate which pathway — or combination of pathways — best fits their objectives and resources.
Clarity and sequencing can provide stability. The aim is not to predict the future, but to position the organization to adapt as conditions evolve.
“Strategy in the Intelligent Economy is not about predicting the future; we believe it is about building the capacity to act with greater clarity as the future unfolds”
Inflection points are moments of choice. While delay can entail opportunity costs, thoughtful, evidence-based decisions — grounded in data, timing, and disciplined execution — can help preserve flexibility and resilience.
