Key takeaways
- AI growth is accelerating across the artificial intelligence market, shifting from cost efficiency to a central driver of growth in multiple industries.
- Adoption of AI technology is fueled by digital transformation, rising customer expectations, and the need for resilience in volatile markets.
- Machine learning advancements are enabling new business models, not just incremental gains.
- The industries that benefit most will be those with high data density, recurring interactions, and margin pressure. Industries with thin margins operate under constant cost scrutiny, where even a small improvement in efficiency can have an outsized impact on profitability. In these sectors, AI helps identify hidden inefficiencies, streamline operations, and enhance decision-making, turning what were once marginal gains into meaningful advantages that strengthen competitiveness and long-term resilience.
- To realize value, executives must embed AI into commercial excellence, rethink monetization, and invest in workforce transformation.
Artificial intelligence is no longer a futuristic experiment. It is embedded in systems, shaping insights, customer journeys, and the strategies that separate leaders from laggards. For senior executives, the question is clear: how do you turn AI growth into sustained business advantage?
At Simon-Kucher, we see AI not as an add-on technology, but as a catalyst for commercial reinvention. Success lies not just in deploying AI tools, but in aligning pricing, packaging, and governance to capture the value they create.
Understanding AI expansion
The artificial intelligence market is scaling at unprecedented speed. By 2030, AI could add over $15 trillion to global GDP, with projections of market size growth through 2025 pointing to consistent double-digit gains.
Industries are already feeling the impact. In finance, AI technology enhances fraud detection and enables personalized advice. In healthcare, predictive models accelerate diagnostics and treatment pathways. In consumer markets, personalization engines and dynamic pricing are shaping customer expectations. Across all of these, AI is shifting from a cost lever to a growth engine.AI
Growth: The numbers and the drivers
In our Global Software Study 2024, software executives reported an average expected revenue uplift of 18% from AI-enabled features within two years of launch. Yet many also acknowledged gaps in monetization discipline.
Similarly, our Global Software Study 2025 found that while 76% of companies had launched AI features, fewer than half had developed more than one pricing model to capture value. Fewer than one in five reported revenue impact exceeding 10%.
The drivers behind adoption are clear. Digital transformation has become operational hygiene, customer expectations for personalization are escalating, and operational volatility is forcing leaders to seek predictive resilience. For boards, AI has moved from optional to essential.
Machine learning advancements and new business models
The leap in machine learning advancements is enabling entirely new business models. Computer vision systems in manufacturing can now predict defects in real time. Financial institutions use predictive analytics to anticipate market shifts. Conversational AI tools are handling nuanced customer service interactions at scale.
But the most profound change is not doing things better - it’s doing new things altogether. AI enables adaptive pricing, products that evolve with user behavior, and operations that self-optimize.
Our Industrials and Business Services Value Creation Study 2025 shows that more than 80% of companies in these sectors expect digital (including AI) to be the top driver of value creation.
AI trends and predictions
Looking forward, three themes will dominate:
- Sector-specific solutions: Healthcare, insurance, and manufacturing industries will see increasingly tailored AI applications.
- Generative AI beyond content: From product simulation to R&D ideation, new forms of innovation will emerge.
- Commercial rigor as a differentiator: Firms that adopt hybrid or value-based monetization models will capture far more upside than those defaulting to usage-only approaches.
As we highlight in our work on AI strategy , success requires moving beyond experimentation to scale, with a focus on measurable outcomes and monetization.
Which industries will benefit most from AI technology?
Not all industries are positioned equally. The most advantaged share three traits: abundant data, frequent decision-making, and recurring customer interactions.
- Software & SaaS: High-frequency product usage and clear ROI make AI a natural fit. Executives expect double-digit revenue uplift from new AI features.
- Financial Services: AI improves fraud detection, underwriting, and customer personalization - areas with significant revenue and risk implications.
- Healthcare & Pharma: AI supports precision diagnostics and outcome-based contracting, moving the sector toward value-based care. Our work on payer contracting in pharma shows how AI is accelerating this transition.
- Industrials & B2B: Predictive maintenance, smart supply chains, and dynamic pricing can unlock margin and agility, though execution must be careful to preserve trust.
- Energy & Utilities: AI-driven optimization reduces waste, improves predictive maintenance, and enables more dynamic customer offerings.
These sectors benefit not just from technology readiness, but from the structural importance of data and decision density in their economics.
Customer experience reimagined
One of the clearest benefits of AI lies in customer experience enhancement. In retail, recommendation engines drive a growing share of sales. In telecom, churn prediction allows proactive intervention. In B2B, AI insights help account managers tailor value propositions in real time.
The strategic advantage here is better service combined with greater differentiation. Companies that embed AI across the customer journey secure loyalty and trust while creating new opportunities for revenue growth.
Marketing strategies in the age of AI
Marketing is evolving rapidly. AI-driven marketing strategies are replacing static campaigns with adaptive journeys, updated in real time based on customer behavior.
Dynamic pricing is a prime example, balancing profitability with satisfaction through instant calibration. Sentiment analysis provides live feedback loops that help executives adjust positioning before negative perceptions take hold.
But monetization matters. It’s crucial to move toward value-based pricing in the age of AI, aligning price to customer outcomes, not usage. Companies that adopt these models will be better positioned to capture sustainable value.
Transforming the workforce
The workforce implications of AI are nuanced. Automation will reduce repetitive work, but it also creates demand for new skills and hybrid roles. The winners will be those who invest in reskilling, adaptability, and cultural readiness.
Embedding AI into commercial excellence programs ensures adoption is tied directly to growth outcomes, rather than treated as a side experiment. The goal is collaboration, not replacement: human creativity and judgment elevated by AI augmentation.
Market size and strategic value
The market size of AI is expanding quickly, but the true differentiator lies in monetization. Many organizations invest in AI, but few align pricing and packaging to extract value.
For executives, this is a warning: market growth benefits those who adapt their commercial systems, not just their technology stacks.
Case study snapshots
- Telecom: A large operator reduced fraud by 80% and saved $17 million annually through predictive AI in maintenance and routing.
- Oil & Gas: Generative AI in tendering increased efficiency by up to 40%, freeing sales teams for higher-value work.
These cases highlight a consistent theme: AI success comes not from pilots, but from embedding technology within pricing, sales, and operations.
These cases highlight a consistent theme: AI success comes not from pilots, but from embedding technology within pricing, sales, and operations.
Conclusion
The story of AI growth is ultimately one of transformation.
But technology alone is insufficient. To capture value, organizations must pair AI adoption with commercial discipline: pricing aligned to outcomes, governance rooted in transparency, and reskilling embedded in culture.
The future of work will not be determined by AI tools alone. It will be shaped by the strategic choices leaders make about how to deploy them, how to monetize them, and how to empower people to thrive alongside them. Done right, AI will not simply redefine industries, it will redefine growth itself.
FAQs
What is the expected AI market size by 2025?
Estimates suggest the artificial intelligence market will maintain double-digit growth through 2025, with trillions in potential GDP contribution by 2030.
Which industries will benefit most from AI technology?
Industries with abundant data and recurring decisions, such as software, financial services, healthcare, industrials, and energy, stand to benefit most.
How can AI tools support business growth?
AI tools enable personalization, predictive decision-making, and operational efficiency.
What role does pricing play in AI-driven growth?
Pricing and packaging are critical. Without disciplined monetization, AI adoption rarely translates into profit. Value-based pricing models allow firms to capture upside as customers see tangible results.
How does AI impact the workforce?
AI shifts task portfolios but doesn’t eliminate human value. By automating repetitive work and supporting decision-making, it frees employees to focus on creativity, judgment, and relationship-building, provided reskilling is prioritized.
