Rethinking Business Models With AI

By Sumeet Gupta

As discussed in the survey, AI Radar for Private Equity, companies should expand their value creation lens to consider how AI can reshape their core business models. Companies that are deploying AI technologies at scale are fundamentally rewiring how value is created and captured. We are at an inflection point of the evolution of AI and expect nearly every company’s competitive position will be influenced — in varying degrees by industry sector — by their use of AI technologies, such as generative AI (“Gen AI”) and advanced analytics.

A thorough examination of “How you sell” (go-to-market and customer engagement channels), “What you sell” (product and service portfolio and value proposition) and “How you create products and services” (corporate, development and delivery operations) can uncover new strategies for addressable market expansion, product and service evolution and operating model transformation. Leaders in AI-driven business model transformation are achieving transformative results by reimagining their entire business architecture to:

• Transform Go-to-Market Capabilities: AI is revolutionizing how companies identify, engage and convert customers through intelligent sales processes. For example, a leading utility company is deploying AI to transform its entire lead-to-cash sales journey — from automated lead scoring that identifies high-potential opportunities, to AI-powered sales assistants that guide representatives through optimal engagement strategies, to dynamic pricing engines that generate customized quotes in realtime. This comprehensive transformation of the sales process has reduced sales cycles by 40% while increasing conversion rates by 25%.¹
• Innovate Product and Service Portfolio: AI enables companies to create entirely new offerings and enter untapped markets through AI-native products and services. For example, ServiceNow’s transformation from an IT service management company that provided basic ticketing and workflow automation to an enterprise AI platform that delivers intelligent automation across HR, customer service, security and IT operations has opened entirely new market segments to serve enterprise-wide needs. This evolution has not only expanded its addressable market — from IT service management ($30 billion) into the broader enterprise software market (more than $200 billion) — but also resulted in 85% revenue growth and 90% customer retention rates as customers adopt these new AI-powered solutions across their organizations.²
• Reinvent Production Economics: AI fundamentally transforms the unit economics of how products and services are created and delivered at scale. UnitedHealth Group’s AI platform has revolutionized its healthcare delivery operations by automating administrative processes, optimizing care coordination and reducing fraud and waste. This operational transformation has resulted in a 30% reduction in delivery costs while simultaneously improving patient outcomes by 45%.³

New Rules of Value Creation

The rules that have governed business value creation for the past century are being rewritten in months, not years. In our analysis of more than 200 companies deploying Gen AI at scale, we’ve observed a fundamental rewiring of how value is created and captured.

For instance, in FTI Consulting’s survey of private equity companies, Figure 1 notes that 59% of company leadership expect that AI will drive significant value creation. This isn’t merely a technological shift — it’s a complete reformation of business fundamentals. Companies that grew up in the digital era like Nvidia, Microsoft and ServiceNow have seen their market capitalizations surge, not just because they’re selling AI technology, but because they’ve gone further and mastered these new rules of value creation.

Some of the traditional metrics of competitive advantage — economies of scale, brand moats and operational excellence — are being rapidly superseded by new forces: the velocity of AI learning loops, the depth of data networks and the breadth of AI-enabled ecosystem orchestration. For executives, understanding these new rules isn’t just about survival — it’s about unleashing unprecedented value creation potential. These new rules of value creation manifest across three fundamental shifts:

Figure 1 – AI Driving Significant Value Creation

CEOs face three critical questions:

• How do we move beyond using GenAI for efficiency gains to fundamentally reimagining our business model?
• How do we build the organizational capabilities needed to continually innovate with AI?
• How do we ensure our transformation creates a sustainable competitive advantage?

The AI-Powered Business Model Innovation Journey

We arrive in a new era of transforming business models and organizations by leveraging the power of Gen AI. An AI-powered business model is an organizational framework that fundamentally integrates AI into one or more core aspects of how a company creates, delivers and captures value. Unlike traditional business models that merely use AI as a tool for optimization, a truly AI-powered business model exhibits distinctive characteristics, such as self-reinforcing intelligence, scalable personalization and ecosystem integration.

There are three parts on the journey to achieving this goal:

Define Target State — Based on your current state, strategic objectives and market position, determine where your end state lies and which of the following archetypes describes where you want to be:

• Enhancer: Best for organizations seeking operational efficiency with minimal disruption
• Adapter: Suited for companies ready to modernize their operating model
• Reinventor: Appropriate for businesses positioned to create new AI-driven value propositions
• Orchestrator: Optimal for market leaders capable of orchestrating industry-wide platforms

Identify AI Role for Success — The role AI plays in your organization should align with your chosen business model target state or archetype, as shown in Figure 2, creating a coherent transformation strategy:

• Efficiency Generator: You’re using AI to optimize existing processes (e.g., automated customer service responses, predictive maintenance)
• Capability Amplifier: You’re reconfiguring operations with AI (e.g., AI-powered sales forecasting, intelligent supply chain routing)
• Value Creator: You’re creating new AI-centered offerings (e.g., AI-first products, autonomous services)
• Market Transformer: You’re building AI platforms that transform market dynamics (e.g., industry-wide AI marketplaces)

Plan Transformation Journey — Develop a roadmap that bridges your current and target states:

• Identify capability gaps between current and target archetypes
• Establish a funding model to prioritize investments in technology, talent and organizational change
• Set clear milestones and metrics for tracking progress
• Define quick wins to build momentum and longer-term strategic initiatives

Figure 2 – Business Model Types and AI Roles for Success

Successful Execution Can Be Difficult

We just discussed the overall journey, the target state for the transformation and AI’s role in it. However, success not only requires great planning, but also strong execution. As an organization moves through its AI-powered business model innovation journey, it must systematically consider the eight essentials of AI-driven business models (Figure 3) and include a holistic assessment of current state capabilities, identification of AI innovation opportunities and development of a well-defined map of the transformation journey. Following this, rapid innovation sprints should be conducted to translate strategic visions into tangible results that validate the identified AI opportunities and de-risk at-scale deployments.

Figure 3 – The Eight Essentials That Determine Success With AI-Driven Business Models

The result: a set of actionable initiatives with clear business model transformation objectives (see below),⁴ implementation plans and success metrics. In working with clients, we have found this rapid execution approach highly effective in operationalizing the new approaches to business models.

Conclusion: Charting Your AI Transformation Path

The transition to AI-powered business models represents both an unprecedented opportunity and a complex challenge. Success requires:

• Clear-eyed assessment of your current position along the transformation spectrum — from Enhancer to Orchestrator
• Strategic alignment of AI roles with your business model innovation goals
• Development of a comprehensive vision that bridges current capabilities with future ambitions
• Careful execution through proven frameworks and rapid innovation cycles

While the potential rewards are compelling — from operational efficiencies to entirely new value propositions — the journey is complex and fraught with pitfalls, not least from existing barriers. Organizations must navigate stakeholder alignment, technical implementation, market integration and ROI realization challenges while maintaining business continuity.

Looking ahead, the stakes will only increase as:

• AI converges with other transformative technologies
• AI capabilities become more democratized
• Business models evolve from individual applications to integrated ecosystems

The organizations that will thrive in this AI-first future are those that begin their transformation journey today with clear strategy and strong governance to navigate the technological, organizational and strategic challenges of AI transformation.

The question is no longer whether to embrace AI-powered business models, but how to execute the transformation successfully while managing risks and maximizing value creation potential.

Reprinted with permission of FTI Consulting.