The era of unchecked exploration has ended, replaced by financial pragmatism — a reaction to misaligned expectations, where unrealistic or poorly defined ROI targets now drive the demand for immediate returns.
The constraints are clear: less budget, more accountability, faster timelines. Innovation teams face proactive involvement in core business growth rather than abstract exploration. Fancy thinking is no longer fashionable, nor feasible.
Most organizations have shifted their innovation pipelines toward Horizon 1 innovations: be closer to the core and deliver short-term results. The tolerance for multi-year experiments without commercial traction has evaporated. This creates structural neglect of longer-term horizons. Horizon 3 ideas—bets placed five years out—are being abandoned because they feel like distractions to organizations optimized for quarterly performance.
Yet beneath this pressure lies pragmatic opportunity. When resources constrain, discipline emerges. The question shifts from "What could we explore?" to "What must we deliver?" This forces focus on instruments and approaches that multiply impact without multiplying cost—such as venture clienting that offers the potential of leveraging billions in external R&D spending.
The instruments that survive this environment share common characteristics: they deliver measurable returns within 12-36 months, they leverage external capital rather than consuming internal budget and they apply the discipline of venture capitalists who cannot afford to keep zombie projects alive.
Macroeconomic pressure forces innovation leaders to choose survival strategies. Some demand business involvement before starting any project. Others serve near-term needs to earn permission for longer-term exploration.
Joel Agard, Group Head of Innovation at Zurich Insurance, and Chantelle Murnaghan, Vice President of Product Innovation and Research at Lululemon, operate in different industries with different constraints. Their survival strategies are different too. Joel looks for confirmed senior management sponsorship before starting any project. Chantelle serves the business with near-term wins to earn permission for upstream work the business doesn't yet know it needs.
Joel's team is part of the Strategy Group at Zurich Insurance, directly under the Group CEO, managing an innovation community spanning 25 countries. 2025 started with a directive from senior management: deliver returns. "That was when we shifted the innovation pipeline, or at least the new projects that we started to support, more towards horizon one," Joel notes. "We now focus more on the innovations that are close to the core and should deliver short term incentives."
For many years, Joel pursued an ambidextrous innovation strategy. The goal for 2026 is to stop the fragmentation. Given that goal, Joel set a strict rule. If there is no confirmed senior management involvement, they don't start. The possibility a project will fail or drag on forever and become a zombie project is too high.
Chantelle's portfolio spans multiple horizons. Last year brought unexpected macroeconomic pressures as Lululemon hit a critical inflection point after years of strong growth. Given this pressure, Chantelle adopted the volume control method: the notion of never turning it off, but turning it up and turning it down.
Chantelle has a different stance from Joel. While Joel won't start a project without confirmed senior management involvement, Chantelle serves the business with her Horizon 1 portfolio. She looks to earn permission for upstream work, even with the absence of any business sponsors. For the upstream work, Chantelle leverages government funding for R&D efforts. This approach has enabled 200 projects at half the typical cost.
Executing effectively requires knowing the basics. In an era where AI removes technical barriers, the question shifts from "can we build this?" to "should we build this?".
David Duncan and Tyler Anderson argue that AI forces a critical shift in the innovator's mandate where the primary question is no longer 'Can we build it?' but 'Should we build it?', positioning the Jobs to Be Done (JTBD) methodology as the essential filter for the AI era where organizations must move beyond fuzzy customer profiles to create 'sharp, nuanced pictures' of customer needs.
The default behavior for any customer is to do what they've always done. Changing behavior takes energy, so the catalyst is the "Job." The JTBD language divides into three distinct types: Functional Jobs (practical tasks), Emotional Jobs (emotional states), and Social Jobs (how the customer wants to engage or be perceived).
A coffee shop example illustrates the shift. Through a Product Lens, you're in the "coffee business." Through a Jobs Lens, you ask: Why did the customer "hire" that cup of coffee?
David argues the "fundamental unit of innovation opportunity" is found at the intersection of the Job and the Circumstance. A job itself doesn't define an opportunity, but it's really the intersection of jobs and circumstances that does.
Tyler addresses how AI changes this process. While AI is a powerful accelerator, it introduces risks if used as a replacement for human understanding. Perhaps the most counterintuitive insight: the speed of AI development has forced his team to move slower in the definition phase.
Translating JTBD insights into scaled innovation requires programs that connect strategy, culture, and execution. Most innovation efforts fail because they pull one lever in isolation rather than designing the entire ecosystem.
Most companies adopt one methodology at a time. They set up an open innovation team to scout startups, or they practice lean to speed up MVPs, or they launch a greenhouse. Each effort makes sense in isolation, and each one tends to fall short for the same reason: it is one lever in a system that requires several to work together.
Paul Campbell and Steffen Bartschat's Innovation Canvas is designed to fix that. Inspired by business model thinking, it forces leaders to look at the entire innovation ecosystem before optimizing any individual part of it.
Two critical bookends frame the canvas: Strategy and Leadership (top—the guiding force defining where innovation fits) and Culture (bottom—the operational reality of how work gets done). Between these lie actionable levers: Design Thinking, Lean Innovation, Business Model Innovation, Open Innovation, Venturing, Greenhouses, and Listening Posts.
When it comes to culture, this unpacks into Principles (unchangeable core values like "Do no evil") versus Practices (operational habits—depreciation schedules, inventory requirements, HR policies). Practices, on the other hand, can be changed. You can change finance depreciation and HR policies. By separating these, innovation leaders diffuse resistance—they aren't attacking the company soul, just updating the operating manual.
The Innovation Scorecard rates proficiency in each canvas box. A company wanting to excel at Open Innovation needs Lean Innovation capabilities to match startup speed and Business Model Innovation to monetize partnerships. If those things aren't in place, you might never get your startup program off the ground.
Today’s constraints demand tapping into the vast ecosystem of external venture capital, rather than relying solely on internal R&D.
Fabian Dudek adds perspective by demonstrating that corporations can tap into the vast external venture capital ecosystem through startup collaboration. Drawing from an analysis of over 250,000 corporate-startup relationships, systematic collaboration drives measurable financial performance, with companies leveraging up to 7.5 times their R&D budget through external partners.
The dominant model has shifted. Historically, corporations engaged with startups by starting accelerators or investing directly. Today however, the most effective way is simply using the startup's solutions. Startups have already invested millions to make their solutions good. Owning shares helps financial returns, yet doesn't necessarily optimize your operations: using a startup solution does.
Critically, the procurement bottleneck is a major hurdle. For this reason, mature organizations create a procurement fast track—a contained, safe zone for experimentation defined by specific constraints. Moreover, portfolio thinking proves value to leadership. Treat POCs like a VC portfolio—don't bet on one, bet on a cluster.
Venture clienting promises access to external innovation, but the gap between that promise and reality is where most programs die—in procurement mazes, silo conflicts, and pilots that succeed but never leave the sandbox.
Silke Grimhardt reveals that pilots die from three predictable causes: innovation disconnected from business need, procurement and legal roadblocks, and solutions that never leave the sandbox.
The recommended process to resolve these failures follows a clear flow: Discover, Purchase, Pilot, Adopt. The Discover Phase interrogates business units to validate pain points. The Purchase Phase navigates legal and procurement roadblocks. The Pilot is often not the biggest problem, because when everything is set, it just runs. The real challenge resurfaces when the pilot succeeds and needs integration. In view of this, organizations utilize the Adoption Cube—assembling a team of "adoption owners" who are dedicated people from crucial functions helping bring the startup into the company.
Venture clienting accesses external solutions for immediate needs, but building future relevance requires owning Horizon 3 bets—the five-to-ten-year ideas that feel like distractions.
Venture building comes in to create the protected space where those bets can develop without being killed by quarterly optimization. Within Sennheiser, Sofia Brazzola operates a venture building studio, operating on a "dual engine setup" and dividing focus between strategic foresight (to identify preferable and probable scenarios five to ten years out) and venture sprints (to validate ideas through short, concise design sprints).
Three hard-earned lessons emerge. Driving Horizon 3 innovation requires a "ring-fenced budget" and domain expertise that explicitly sits outside the core. Innovators must convert high-level trends into actionable insights and venture theses that stakeholders can say yes or no to. And finally—exploration looks expensive until you measure the alternative, which is irrelevance.
The instruments are clear: internal programs, external collaboration, venture building. Yet none of these matter if innovation teams cannot measure the value they create in language finance understands. Survival requires connecting innovation activity to CFO priorities through metrics that prove impact rather than activity.
Dan Toma proposes a "minimum viable" set of metrics offering high impact relative to the investment needed to track them. These are 12 key indicators structured across "three plus one layers."
The layers correspond to different organizational decision-making levels: the Strategic Layer (addresses the board's needs—"Is our innovation system working?"), the Funnel Layer (aggregates data from below—"How healthy is our portfolio?"), the Tactical Level (focuses on the team's needs), and the Culture Level (encompasses everything—"Do we have the right culture needed to innovate?"). Connectivity between these layers is essential.
Implementing innovation accounting should be treated as a change management initiative. It’s best to start from the KPIs you already track.
Measuring innovation through aggregated metrics provides portfolio visibility, but proving value for individual initiatives demands a single financial metric that speaks directly to enterprise value from the moment an idea is conceived.
Simon Hill introduces a new metric—Expected Value (XV)—designed to bring discipline, transparency, and predictive power to innovation portfolios. In sports, there is a metric called Expected Goals (xG). Innovation needs its own version: Expected Value (XV).
Simon's formula for XV is built on four specific dimensions: Confidence Reality Check (weighted 0 to 100%), Predicted Value (currency-denominated economic output that changes as new data comes in), Validated Urgency Only (time sensitivity as a multiplier, typically ranging 0.5 to 1.5), and Strategic Fit Filter (answering "Is this a good idea for us?").
Calculating the Expected Value is only half the battle. The other half is understanding what you're spending to generate that value. This is the metric of Innovation Efficiency. You cannot sustainably spend $100 to create $1 of expected value.
Securing sustained investment requires fundamentally changing where the money comes from. Operating budgets force quarterly thinking; balance sheet capital enables long-term growth.
Elliott Parker argues that the type of funding you receive determines the type of innovation you can pursue. To unlock transformative growth, you must fundamentally change where the money comes from by accessing balance sheet capital rather than operating budgets.
Transformative innovation is not an operating activity. When innovation is funded as OpEx (Operating Expense), it's a tax on the operating business. The solution is finding ways to fund innovation as CapEx (Capital Expenditure). Companies are often sitting on mountains of cash on the balance sheet while managing operating expenses down to the penny.
A specific mechanism unlocks balance sheet capital: Venture Building. By designing and launching external ventures—independent entities outside the corporation—you allow the corporation to fund the activity with CapEx rather than OpEx.
Validating value through market signals solves the traditional struggle of trying to convince executives through internal metrics. External venture building solves this, since you're not the one assigning value to it… the market is.
The horizon for delivering short-term growth extends far beyond surviving the next budget cycle. What we're witnessing in 2026 is not a temporary contraction but a permanent evolution in how corporations fund and execute and measure innovation.
What Corporate Innovation Teams Need to Do to Succeed in 2026
Advice from Expert members of the Community
Sebastian Müller, Founding Partner Strategy and Ventures at MING Labs
Over the past decade, companies created innovation teams and gave them freedom, protection, and autonomy. A big issue with this is autonomy without ownership. Whereas startup teams learn because survival is at stake, corporate innovation teams, by contrast, learn precisely because nothing is on the line. This is a gap that we can’t ignore in 2026.
AI has removed most operational excuses, but decision avoidance remains. In this environment, the job of an innovation team is no longer to generate options, but to force decisions. That means innovation teams should be accountable for clear, consequential outcomes—typically one of three: kill an initiative decisively, commit real resources to scale it, or transfer full ownership into the business or a new venture.
Importantly, success should be measured by how quickly teams make themselves unnecessary—by transferring real ownership, budgets, and accountability.
If an innovation team cannot clearly name the decision it is accountable for—and the consequence if it gets it wrong—it should not exist in its current form.
Alan Cucknell, Director at Ignite Exponential
My conclusion for 2025 was that, in many large companies, real innovation progress and impacts are still frustratingly slow. Many corporates assume that digital technologies like AI and the ability to work from anywhere will make their organisations more productive and accelerate innovation. In reality, that means that we’re busier than ever – especially senior leaders.
AI is bringing more data, more information and more analysis than we can handle; all in a format which, for a good reason, us humans don’t yet fully trust. Ironically, the result of this is that key decisions get delayed and the impact of innovation stagnates.
A return to intentionally-designed, in person workshops can cut out unnecessary distraction, create a joined-up understanding and enable the organisation to make tangible innovation decisions to unlock impact.
My advice for corporate innovators in 2026: start with people, not technology; keep testing in the real world while letting AI fuel your work; and when it comes to prototypes and experiments, act first and ask for forgiveness later.
Daniel Martin Callizo, Managing Partner at NOBA Ventures
Succeeding in 2026 is less about bold declarations and more about disciplined choices, grounded in real-world evidence. Several resolutions reflect commitments that innovation teams must make to remain effective.
Firstly, we will operate in the Goldilocks zone and prioritize ideas the business can absorb. In this zone, adjacent initiatives can reuse existing assets, channels, and customers, while benefiting from faster and more flexible ways of working.
Also, we will clearly separate AI governance from AI application. AI teams will own governance, infrastructure, and risk, whereas innovation teams will own application, working on how AI reshapes value propositions, workflows, and business models.
When it comes to startups, we will engage with them only when there is a credible route to value creation and when internal teams are ready to absorb what works. If that path is unclear, we will not start. We will also use vibe coding and AI-backed prototypes to test products that feel real. The basis for our decision-making will be near-production prototypes, not low-fidelity tests that delay learning.
Sertaç Oral, Founding Partner at Global Vision for Innovation
By 2026 the famous motto "innovate or die" is no longer a cliché—it is a survival recipe. The era of "Innovation Theater"—sticky notes, bean bags, and endless ideation—is finally dead. Personally, I am very happy about it. To succeed in this harsh climate, innovation teams must pivot immediately.
Firstly, stop chasing Horizon 3 moonshots. In 2026, you must embed directly into core Business Units rather than acting as a separate entity.
You must use AI tools to make your processes more efficient. But beyond tools, you must execute real-life AI solutions across the company; from production to quality, from operations to sales and marketing and other back-office areas. Don't be shy on using expert support for executing and leading this great shift in mindset. Remember that only a handful of companies have the required human capital to make this shift.
Finally, seek orchestration support from industry experts to navigate business model disruption, and use "Revenue Impact", "Cost Savings", "Time to Market" and "Kill Rate" as the only metrics that matter now.
