Most companies ask: “How do we use AI to do what we already do, but faster and cheaper?” The ones looking further ahead to renewal and strategic growth ask: “What levers of growth can we now pull and what new services and revenue streams to create by leveraging AI, in a way that was impossible before?”
Same technology challenge (“embed AI”). Different question. Different financial outcome.
I’ve been looking into what 2025 research on this topic tells us — from BCG, McKinsey, Deloitte, and Accenture (covering more than 7,500 firms). They all converge on this: companies that aim AI at revenue creation dramatically outperform those that aim it at cost reduction. [1][2][3][4]
Three Modes of AI — And Where the Money Is
I think about AI strategy in three modes:
Mode 1: Same but more efficient. AI can automate a lot of what you already do, and do it quicker. Copilots, task automation saves time and can reduce cost by 10?15%. This is where ~80% of AI budgets go. However, this is table stakes as competitors match it next quarter.
Mode 2: Redesigned ways. A core function and associated customer journey gets rebuilt end-to-end around AI. Processes and operational workflows get redesigned to reduce customer friction, make processes and CX better, hence improving acquisition, retention, upsell, etc. This can lead to 30?50% revenue improvements. This is where AI advantage starts to drive growth.
Mode 3: New offerings and new money. Designing products or services that did not exist before, leveraging AI. New product categories entirely. New pricing/revenue models. Different ways for serving new customer segments at scale. This is where competitive moats get built.
BCG calls these modes Deploy, Reshape, and Invent. Mode 1 protects today’s margins. Modes 2 and 3 create tomorrow’s revenue. Everyone focuses on Mode 1. The rest of this article is about Modes 2 and 3.
The Evidence: Revenue Beats Savings, Every Time
McKinsey’s “AI high performers” — the ~6% of companies attributing 5%+ of EBIT to AI — are 3x more likely to set growth and innovation (not just efficiency) as AI objectives. They also redesign workflows rather than just deploying tools. [1]
BCG’s “future-built” companies (top 5%) achieve 5.3x the revenue increase from AI vs. laggards. They allocate 80%+ of their AI budget to Modes 2 and 3, while laggards put 56% into Mode 1. [2][5]
Deloitte found 74% of companies aspire to grow revenue with AI — but only 20% have done it. Only 34% are actually reimagining products, processes, or business models. [3]
Accenture found companies with AI-redesigned operations achieve 2.5x higher revenue growth. [4]
Every data set tells the same story: cost savings are the consolation prize. Revenue creation is the game.
What Mode 2 Looks Like on Monday Morning
Mode 2 isn’t abstract. It’s a specific decision: pick one core function/area where CX is full of friction, growth is stalling or targets are not achieved and redesign it to make it better, leveraging what AI makes possible.
A global beauty company (BCG client) didn’t add a chatbot. They redesigned the entire online customer journey — AI consultation, real-time personalization, unified data — across 20+ markets. Result: $100M expected incremental revenue, 2x traditional e-commerce ROI, deployed in under 12 months. [2]
Some practical steps to follow: - Pick your highest-revenue driving lever today (customer experience/NPS, cross-sell etc) - Ask: “If we redesigned this entire journey and process from scratch today, with AI as a core capability, what would it look like?” - That answer — not the current process with AI bolted on — is your Mode 2 target - Staff it with a cross-functional team with mandate to change the workflow, not add tools - Set a revenue or margin target, not just a cost target
McKinsey confirms: workflow redesign is the single strongest predictor of whether companies see EBIT impact from AI. Not better models. Not more pilots. Redesigned work. [1]
What Mode 3 Looks Like on Monday Morning
Mode 3 is a different question: “What valuable thing can we monetize better / in addition, that was impossible before AI?”
Adobe’s Firefly is the clearest proof point. Adobe didn’t optimise Photoshop. They created a new product category — AI-native creative tools with credit-based pricing ($10?$200 tiers). AI-first products hit $250M+ ARR by end of FY2025. AI-influenced revenue now exceeds a third of total business. [6]
Some practical steps to follow: - Bring together your product, insight and commercial leaders (not just your AI team) - Ask: “Given our data, our customer relationships, and our domain expertise — what new service opportunities become viable to monetize now that AI is here?” - Pilot the proposition as well as pricing model, not just the technology. If you can’t charge for it to create new revenue streams, it’s not Mode 3. - Look at your existing customer pain points and product ideas “paused” before through the lens of “what was too expensive to solve before AI reduced the unit economics?”
Deloitte research shows that AI ROI Leaders are 2x more likely to define success as “revenue growth opportunities” and “business model reimagination” vs. peers. [8]
The CEO Question
This shift doesn’t happen bottom-up. Mode 2 and 3 decisions involve pricing, business model, customer strategy, and organizational redesign. Those are CEO-level calls.
Deloitte found only 10% of companies have the CEO as primary AI leader. [8] McKinsey found high performers have visible CEO commitment 3x more often. [1] BCG found that among laggards, “top management may talk the talk, but won’t articulate any clear value ambition.” [2]
The most valuable challenge to own: The CEO (or Chief AI/Innovation Officer with CEO backing) should own the answer to one question: “What new revenue will AI create for us in the next 18-24 months?” That question should appear in the next board deck with a specific financial target. The AI team’s mandate should shift from “find savings” only to “build revenue” — even if the savings mandate continues alongside it.
The Three-Question Diagnostic
Before your next AI investment, answer these:
1. What percentage of your AI budget targets new revenue vs. cost reduction? Below 30% on revenue = overweight on Mode 1. Shift at least a third of spend toward Modes 2 and 3 this year.
2. How many AI initiatives are running — and how many are generating revenue? More than five running, zero making money = consolidate. Leaders run 3.5 focused bets, not 6.1 scattered ones. [5]
3. What growth levers can you improve and what new revenue streams can you create today, that was impossible 18 months ago? If you can’t answer in one sentence, that’s not a failure — it’s a signal. That question is worth a dedicated strategy session this quarter.
The Window Is Closing
Mode 1 commoditizes fast. Every copilot you build, competitors replicate next quarter. Mode 2 and 3 initiatives take 12+ months to build and are hard to copy. The companies building them now compound their advantage every quarter.
BCG’s top 5% achieve 5.3x the revenue increase from AI. [2] Your AI strategy is either designed to create revenue that exists tomorrow — or to protect margins that exist today. The winners chose revenue.
Stop Piloting AI to Save Costs. Start Building AI-native Workflows, Customer experiences and Business models to Make More Money.
Sources [1] McKinsey, “The State of AI in 2025,” Nov 2025. ~2,000 executives. ~6% are high performers; 3x more likely to pursue transformation; workflow redesign is #1 EBIT predictor. [2] BCG, “The Widening AI Value Gap,” Sep 2025. 1,250+ firms. Top 5% achieve 1.7x revenue growth, 3.6x TSR, 5.3x revenue increase; 70% of value in core functions. [3] Deloitte, “State of AI in the Enterprise,” 2026 edition (surveyed Aug-Sep 2025). 3,235 leaders. 74% aspire to revenue from AI; 20% achieve it; 34% deeply transforming. [4] Accenture, “Reinventing Enterprise Operations with Gen AI,” 2024. AI-led companies achieve 2.5x revenue growth; 64% struggle to change operations. [5] BCG, “Where’s the Value in AI?” Oct 2024. 1,000+ CxOs. Leaders: 3.5 vs 6.1 initiatives; laggards put 56% in Mode 1; leaders put 80%+ in Modes 2/3. [6] Adobe Q4 FY2025 Earnings, Dec 2025. AI-first products >$250M ARR; AI-influenced ARR >1/3 of total business. [7] McKinsey, “Evolving Models and Monetization in the AI SaaS Era,” Sep 2025. Adobe’s evolution from embedded to standalone AI monetization. [8] Deloitte, “Turning AI into ROI,” Nov 2025. 1,854 executives. ROI Leaders 2x more likely to frame success as revenue growth; only 10% have CEO as primary AI leader.