The Growth Gap Imperative: Redesigning Business Models for AI, Digital Ecosystems, and Sustainable Expansion
The Growth Gap Imperative: Redesigning Business Models for AI, Digital Ecosystems, and Sustainable Expansion
Business model redesign / AI business transformation / Growth gap strategy
26 December, 2025
Many leadership teams are discovering that their most successful business model has quietly become their biggest constraint. Revenue is still coming in, efficiency programs still deliver savings, but every planning cycle makes one thing clearer: the current model cannot carry the growth ambitions of the next decade. The result is a structural growth gap that cannot be closed by cost cutting, incremental product updates, or “more of the same” in new markets.
This article explores how C‑level leaders can diagnose that growth gap, redesign their business models for a world shaped by AI, digital ecosystems, and convenience‑driven customers, and build a practical, governance‑anchored path to sustainable business growth.
Why your current business model is losing power
Most incumbent business models were designed for a world where:
- Technology cycles were slower.
- Customers accepted complexity if the product was technically superior.
- Value chains were linear and largely under a single company’s control.
Today, several forces are steadily eroding the power of those models:
- Digital platforms reset expectations around speed, transparency, and ease.
- AI‑driven services make personalization and prediction feel normal, not premium.
- Ecosystems and partnerships blur industry boundaries and ownership of the end‑to‑end experience.
When these forces meet a legacy model, warning signs appear:
- Revenue growth becomes heavily dependent on price increases rather than genuine expansion.
- New offerings struggle to scale because they are forced into old pricing, sales, and governance structures.
- High‑potential digital or data initiatives sit on the side, disconnected from the core P&L.
The question is no longer whether the current model will weaken—it is whether leadership will redesign it before external disruption or internal stagnation does the job instead.
A clear, executive‑level view of your business model
A business model is not a slogan, a canvas, or a list of initiatives. For C‑level leaders, it helps to think of it as an integrated system answering four fundamental questions:
Who is the customer and which “job to be done” are we solving?
- What outcome do they really care about?
- How do they want to feel before, during, and after interacting with us?
What is our value proposition?
- Why should they choose us over alternatives or workarounds?
- Are we offering a product, a service, a platform, an outcome—or a combination?
How do we make money (profit formula)?
- How is revenue generated (transactions, subscriptions, usage, performance‑based)?
- What cost structure, margin profile, and capital intensity sit behind that?
Which capabilities and processes make this work at scale?
- What people, technology, data, and partnerships are essential?
- How do we decide, prioritize, and measure performance day to day?
Leaders often find that once this is articulated clearly, two realities emerge:
- The current model was built for a different customer, under different constraints.
- Major investments in AI, digital, and customer experience are being forced to “fit” an outdated profit formula and operating logic.
That clarity is the prerequisite for deliberate reinvention.
From product logic to “job to be done” logic
The most common mistake in transformation programs is starting with internal capabilities and technologies rather than customer jobs. A product‑centric view asks: “What more can we sell with what we already know and own?” A job‑centric view asks: “What is the most important, under‑served progress our customer is trying to make—and how could we become essential to that?”
For senior leaders, shifting to a job‑centric logic has several implications:
- Market definitions change. Competitors are no longer only those with similar products but any alternative way of achieving the same outcome.
- Innovation briefings change. Instead of “build feature X,” teams are asked to redesign how customers discover, evaluate, use, and pay.
- Investment decisions change. Projects are prioritized based on the importance and under‑served nature of the job, not the internal sponsorship of a function.
AI and advanced analytics can greatly enhance this work. By integrating data from usage patterns, support interactions, and external signals, leaders can see what customers are actually trying to achieve, where friction is highest, and which segments exhibit “early signals” of changing jobs.
The rise of the convenience‑ and experience‑driven customer
Across both B2C and B2B contexts, decision‑makers gravitate toward offers that:
- Reduce the cognitive load of choosing between complex options.
- Minimize time spent on low‑value tasks such as administration, coordination, and troubleshooting.
- Provide predictable outcomes through clear service levels, automation, and proactive support.
This is reshaping what “good” looks like in many industries. Customers now expect:
- Seamless digital journeys from discovery to renewal.
- Transparent pricing and flexible payment models.
- Context‑aware interactions that feel tailored, not generic.
A business model that still assumes:
- Heavy manual steps,
- Fragmented channels, and
- One‑size‑fits‑all contracts
will struggle to command a premium or retain loyalty—even if the underlying product is technically excellent.
AI amplifies this shift. Intelligent assistants, recommendation engines, and automated workflows make it easier than ever for customers to:
- Compare alternatives in real time.
- Automate parts of their own processes without vendor involvement.
- Switch providers when friction outweighs perceived value.
Leaders must therefore treat user experience, accessibility, and digital readiness not as “front‑end polish” but as structural components of the business model.
AI and digital readiness as business model design questions
Many organizations see AI as a technology layer to be added to existing products and processes. Executives with a more strategic view treat AI and automation as levers that can fundamentally reshape the business model:
Value proposition:
- Moving from reactive service to proactive, predictive outcomes (e.g., from scheduled maintenance to AI‑driven “no downtime” commitments).
- Enhancing personalization at scale in pricing, configuration, and support.
Profit formula:
- Changing cost structures through automation of routine tasks.
- Creating new revenue streams based on data‑driven services, insights, or performance‑based contracts.
Capabilities:
- Building internal AI fluency and governance, not just buying tools.
- Integrating data sources across silos to enable meaningful models.
Processes:
- Redesigning decision‑making so that human and machine intelligence complement each other.
- Embedding experimentation, monitoring, and continuous improvement in how AI is deployed.
The key is to move from isolated pilots to coherent design. Without that, organizations end up with scattered AI use cases that look innovative individually but do not move the needle on growth, margin, or customer experience.
Redesigning the profit formula for the digital age
One of the hardest shifts for incumbents is changing how money is made. Traditional models often rest on large upfront sales, volume‑based discounts, and long replacement cycles. In contrast, digital‑ and AI‑enabled models increasingly rely on:
- Recurring revenue (subscriptions, as‑a‑service offers).
- Usage‑ or outcome‑based pricing.
- Bundling of product, service, and digital capabilities into integrated solutions.
This has deep consequences for:
- Cash flow and capital allocation: Revenue may be more stable but ramp up differently.
- Sales incentives: Compensation must reward long‑term value, not just initial deals.
- Risk sharing: Contracts may tie revenue to jointly defined performance metrics.
Leaders who treat the profit formula as non‑negotiable will unconsciously limit what is possible in AI, digital, and experience innovation. Those who are willing to re‑engineer it open room for entirely new forms of value creation.
Building the capabilities and processes of a modern model
Even the most compelling design will fail if the organization cannot execute it repeatedly. For a digitally ready, AI‑enabled, customer‑centric business model, senior executives need to ensure several capabilities and processes are in place:
Data and integration:
- A unified view of customers and assets, not fragmented systems by product, region, or channel.
- Clear data ownership, quality standards, and governance.
Experience design and accessibility:
- Multidisciplinary teams that combine business, technology, design, and behavioral insight.
- Interfaces and journeys that are intuitive, inclusive, and consistent across devices and contexts.
AI and analytics operations:
- Mechanisms to deploy, monitor, and refine models in production, not just in proofs of concept.
- Guardrails for ethics, bias mitigation, and regulatory compliance.
Agile, experimentation‑oriented ways of working:
- Short cycles of testing assumptions about value proposition, pricing, and experience.
- Decision forums that are comfortable with uncertainty and staged investment.
Without these, even a well‑conceived business model remains a slide rather than a system.
Why transformation fails without the right governance
Business model innovation cuts across business units, functions, and time horizons. It changes revenue patterns, cannibalizes legacy streams, and challenges existing power structures. That is why it rarely works if treated as a side project.
Effective governance for business model innovation usually entails:
- A senior‑level growth and innovation board anchored by the CEO or COO.
- Clear growth mandates and guardrails: where the company must explore, where it will not.
- Dedicated budgets for exploration, incubation, and scaling, protected from short‑term cuts.
- Explicit criteria for when an emerging model “graduates,” is reshaped, or is retired.
Crucially, governance must recognize that a fundamentally new model cannot be judged by the same early‑stage metrics as the core. Revenue, margin, and efficiency ramp differently; learning velocity, validated assumptions, and customer traction become equally important indicators in early phases.
Structural separation without strategic detachment
Many leaders ask whether new business models should be built inside the core business or outside it. In practice, the answer is “both, but deliberately”:
- Separate enough to protect new models from legacy constraints (systems, metrics, politics).
- Connected enough to access the assets that make the company powerful (brand, relationships, expertise, distribution).
This can take the form of:
- Dedicated venture units or business‑building teams.
- Joint governance between core and new units.
- Clear rules for when and how integration should happen.
The goal is to avoid two extremes:
- Total separation, where the new unit becomes an orphan without leverage.
- Total integration, where the new model suffocates under legacy processes and expectations.
Making user experience and accessibility strategic, not cosmetic
For senior executives, user experience and accessibility are often associated with interface design. In modern business models, they are strategic differentiators.
A model is more robust when:
- Customers can easily understand what is offered and what value they will receive.
- Digital touchpoints are designed for different levels of digital literacy and device access.
- Interactions across channels feel consistent and coherent, not fragmented.
Accessibility also has a broader meaning:
- Can smaller customers or underserved segments realistically adopt the offer?
- Are terms, prices, and processes transparent and understandable?
- Are physical and cognitive barriers minimized across the journey?
Treating accessibility and experience as structural design parameters, rather than last‑mile enhancements, increases both adoption and loyalty.
Leading from the future, not from the quarter
Under pressure, leadership teams often default to optimizing the next 12–24 months. Yet the most powerful shift happens when executives commit to a disciplined “future‑back” perspective:
- Envision how markets, technology, regulation, and customer behavior may plausibly look 5–10 years from now.
- Identify which parts of the current business model remain valid and which are likely to erode.
- Define a portfolio of potential future business models and growth platforms.
- Work backward to decide what must be started now—capabilities, partnerships, experiments—for those futures to be reachable.
This is not prediction; it is structured preparation. By making the growth gap and future scenarios explicit, leaders create the organizational will to move beyond incrementalism.
Questions for your next leadership discussion
To turn these concepts into concrete leadership action, consider using these questions with your board or executive team:
- Which elements of our current business model (customer, value proposition, profit formula, capabilities) were designed for a world that no longer exists—and where are they actively constraining our growth?
- What are the most important “jobs to be done” for our customers over the next 5–10 years, and where are we still thinking in product categories instead of outcomes and experiences?
- How could AI, data, and automation enable a fundamentally different way of creating and capturing value in our business, beyond incremental efficiency gains?
- If we had to redesign our profit formula from scratch—revenue model, pricing logic, and cost structure—what would it look like in a digital, subscription‑ and service‑oriented environment?
- What governance and structural mechanisms are missing today that would allow us to systematically explore, incubate, and scale new business models alongside the core?
- How will we hold ourselves, as a top team, accountable for building tomorrow’s growth engines—not only for delivering this year’s numbers?
These questions are an invitation to move from “doing some innovation” to deliberately reshaping how the business creates, delivers, and captures value. They set the stage for a clear, focused call to action: a decision by the leadership team to treat business model renewal as a central strategic responsibility, rather than a peripheral, project‑based activity.
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Inna Hüessmanns, MBA
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