How New AI Models Will Impact Businesses

AI’s Structural Impact on Enterprise Value and Credit Worthiness AI is in the process of creating a paradigm shift that will redefine the business model for industry sectors throughout our economy. While many companies will adapt, become more efficient, enjoy revenue growth and reduce their cost structure, others will experience the complete opposite impact. The evolving development and adoption of AI creates a profound transformational and fundamental reconfiguration that will transform how industry operates. Investment managers must also adapt as AI changes the equation for traditional underwriting assumptions that is core to determining a borrower’s future market position, competitive edge, cash flow, earnings and growth; the very foundations for value analysis. In the past, a downturn was often impacted by a cyclical decline associated with a slowing economy, recession or tightening of liquidity conditions that led to dislocation or distress. A structural change, however, is not a temporary or passing condition, but rather a long-term, irreversible development that renders old models obsolete. AI requires asset managers, capital allocators, and corporate executives to evaluate this new risk factor that has previously not been considered. Healthcare, Business Services, Software, and Manufacturing companies will all be impacted by AI with the potential to lower marginal costs allowing for greater scale and stronger unit economics. Upfront R&D and CapEx will be required, so the cost for advancement is not free, yet those caught flat-footed may see their cost per unit become uncompetitive vs. a highly efficient first-mover competitor. Take an enterprise software company for instance where the incumbent who fails to integrate AI sees their business deteriorate with the struggle of a less dynamic operating system, higher churn/deteriorating customer retention, compressed margins and eroded competitiveness. An AI-first software company that offers superior and more efficient products will take ARR from the incumbent. As a Private Credit lender, committing to 5–7-year loans is an eternity as AI alters the value proposition. Capital Solutions providers will be busy as companies adjust to this new dynamic. Stress-testing businesses to model this AI paradigm shift, assessing which companies are insulated from AI, or positioned to leverage AI to drive EBITDA or create a defensible moat represents the questions and quandary one must determine. When evaluating an investment, it’s imperative to understand your downside case associated with a cyclical decline that is stressed for recession or a banking crisis. It is critical that these scenarios are underwritten by experienced investment management teams that have lived through these transitional periods, but we now have one more risk factor that is important to understand and underwrite. Marathon Asset Management's Investment Committee and investment team closely considers AI risks when investing. 

Not every AI initiative moves the P&L. I’ve found it helpful to bucket AI opportunities into three categories; each with a different impact on revenue and margin. 1️⃣ Productivity Add-ons Tools like Microsoft Copilot, Adobe Firefly, and ChatGPT deliver quick wins. Most SaaS platforms now include AI features; and you’re already paying for them. These tools are valuable, and their gains compound over time; but they’re table stakes. Every enterprise should be deploying them to unlock hidden capacity and insight. As CIOs, our job is to ensure the right tools are in place and adopted; so we see real margin expansion, not just impressive demos. 2️⃣ Reimagined Workflows This is where meaningful business impact happens. Your business processes are your capabilities; they define how you create value. With machine learning, we can upgrade those capabilities and strengthen our competitive position. Today, many customer interactions depend on an employee’s individual experience and intuition. But what if every team member could make decisions with the collective intelligence of your best people? Imagine a new customer service agent: as they answer a call, their system recommends the Next Best Action; drawn from machine learning models trained on your historical data and customer patterns. The agent decides whether to follow the suggestion, and the outcome is captured. Over time, the system keeps learning from every decision and result. This creates augmented intelligence; continuously upskilling every employee, improving consistency, and driving measurable revenue uplift through smarter upselling and cross-selling. As confidence grows, you can safely automate lower-risk scenarios, freeing people to focus where relationships truly matter. And when you start blending internal and external datasets, the system becomes even more powerful; a self-learning engine that turns every interaction into a competitive advantage. That’s what it means to move from human experience → machine-augmented performance. 3️⃣ New Business Models At the far end of the spectrum are entirely new models born from AI; like Shopify’s dynamic micro-stores or Netflix’s content optimization. They’re transformative but rare, and often require a willingness to reinvent or even cannibalize parts of your core business. As a CIO, I focus on two or three business areas where re-imagining workflows and applying machine learning can materially move the P&L. That means diving deep into the business model; understanding how value is created and where we can strengthen our competitive advantage. Only then can we translate AI potential into real financial outcomes. That’s where AI becomes more than hype; it becomes a growth engine that differentiates the business. Curious how to identify the best workflows to reimagine with AI? 👉 I’ll explore that in my next post. #AI #DigitalTransformation #CIOLeadership #EnterpriseAI #BusinessGrowth

AI agents built on large language models (LLMs) are rapidly changing business operations. From automating complex workflows to personalizing customer interactions, the impact of AI-driven agents is already profound—but we’re just getting started. What excites me most is how these AI capabilities evolve beyond simple chatbots. We’re now seeing AI agents that can proactively analyze data, execute tasks across multiple systems, and collaborate with teams in real time. Whether it’s a customer service AI resolving inquiries instantly, a sales AI identifying and nurturing leads, or a financial AI optimizing market predictions, these technologies are becoming indispensable across industries. Where AI Agents Will Drive the Most Impact: ✅ Customer Experience: AI agents will provide hyper-personalized interactions, anticipating customer needs and resolving issues before they escalate. This is the next frontier in CX differentiation. ✅ Sales & Marketing: AI-powered prospecting, automated follow-ups, and predictive lead scoring will redefine how businesses engage with potential customers—turning insights into revenue faster. ✅ Operations & Productivity: AI agents will streamline internal processes, handling scheduling, compliance tracking, and even drafting reports—freeing teams to focus on strategic work. ✅ Financial Intelligence: AI-driven market analysis will empower businesses with predictive insights, whether forecasting demand, optimizing pricing, or identifying investment opportunities. ✅ AI-Powered Decision Support: AI agents will automate tasks and provide real-time recommendations, helping leaders make data-driven decisions with greater accuracy and speed. The Competitive Advantage: AI + Human Collaboration The real power of AI agents isn’t in replacing people—it’s in augmenting human capabilities. The most forward-thinking businesses will leverage AI to enhance decision-making, automate routine tasks, and unlock new levels of innovation. As these models become more context-aware and multimodal, expect AI agents to seamlessly integrate across business functions, making real-time recommendations and executing tasks autonomously. The future isn’t just AI-powered—it’s AI-accelerated. Today, businesses that invest in AI agents will gain a lasting competitive edge, increasing efficiency, agility, and customer satisfaction. Are you exploring AI agents in your business? Let’s connect—I’d love to hear how you’re using AI to drive innovation. #AI #ArtificialIntelligence #BusinessInnovation #LLMs #AIAgents #FutureOfWork

AI is taking jobs—just not the way you think. For years, we've been told that AI won't replace jobs—it will just change them. But that's only half the story. The reality? AI is already reshaping industries at an unprecedented pace. →  Big tech firms are already saying they can replace a significant portion of their developers with AI. →  AI-generated content is now competing with human writers at scale. →  Legal research, customer support, financial analysis—AI is automating core tasks faster than expected. The uncomfortable truth: Some jobs will disappear. But here’s where organisations have a choice. They can: 🔴 Automate without foresight—cut costs, reduce headcount, and build rigid AI-driven processes that lack adaptability and human oversight. 🟢 Use AI to augment and evolve jobs—rethinking workflows, creating new roles, and fostering AI-human collaboration to drive agility, innovation, and long-term competitive advantage. 🚨 Where Organisations Go Wrong: • Automating too aggressively → Losing adaptability and human oversight. • Replacing people instead of redefining work → Creating rigid AI-driven processes that struggle to evolve. • Focusing only on cost-cutting → Missing opportunities to drive AI-enabled innovation. 🔴 The Old Model: → Cut jobs to reduce costs. → Automate processes without a long-term vision. → Create a brittle, AI-driven business that lacks adaptability. 🟢 The AI-Resilient Model: → Redesign jobs with AI augmentation in mind. → Invest in AI literacy and workforce transformation. → Build a company that is both automated and adaptable. The real question isn’t if AI will impact jobs—it already is. The question is: Are you designing your organisation for AI resilience or just short-term efficiency?

Breaking Down OpenAI's Latest Innovation: o3 and What It Means for Business The AI landscape just shifted dramatically with OpenAI's new o3 model. As a business leader, here's what you need to know about this game-changing development: 5 Key Business Takeaways: 1) Superhuman Performance: O3 isn't just another AI update – it's outperforming human experts in coding, mathematics, and complex problem-solving. Imagine having a team member who ranks among the world's top 200 programmers. 2) Knowledge Work Revolution: This isn't about automating simple tasks anymore. O3 could transform how we handle high-skilled work in tech, finance, and analysis. Companies need to start thinking about how their workforce roles WILL evolve. 3) Cost Reality Check: Currently, o3 requires significant computing power – taking up to 16x longer than humans for complex tasks. But like all tech, expect these costs to decrease over time. Early adopters might face higher expenses for competitive advantage. 4) Innovation Accelerator: Think faster R&D, quicker product development, and more efficient problem-solving. Smaller companies might soon access capabilities that were previously limited to tech giants. 5) Strategy is Critical: Success with o3 isn't just about adoption – it's about smart integration. Companies need clear AI governance frameworks and implementation strategies. Why This Matters for AI Agents: O3's breakthrough is a game-changer for AI agents. With its advanced reasoning capabilities, agents can now tackle complex, multi-step tasks more effectively. Think of agents that can: * Plan and execute sophisticated business strategies * Adapt to unexpected situations in real-time * Handle complex coding and development tasks autonomously * Make more nuanced decisions based on context * Learn and improve from their experiences continuously The real power comes when these capabilities are combined with automation – imagine AI agents that can not just follow instructions, but truly understand, plan, and execute complex business workflows independently. The bottom line? We're not just watching another tech update – we're witnessing a fundamental shift in what AI can do for business. The question isn't whether to adapt, but how quickly and strategically to do so. Mercer

AI is dramatically reshaping business models. This framework is the foundation of my new LinkedIn Learning course "AI-Driven Business Model Innovation". See below for a brief summary of the 6 domains of AI’s impact on value creation, together with the major driving forces and the capabilities required as business models rapidly evolve. Link to the course - free for LinkedIn subscribers - in comments. DRIVING FORCES 🧠 Driving Forces of AI Evolution We’re at a structural shift in business. AI capabilities are accelerating, costs are falling, and data is becoming a strategic asset. These forces are reshaping the foundations of value creation — demanding that leaders rethink not just what their business does, but how it evolves. SIX DOMAINS OF AI-DRIVEN BUSINESS MODEL INNOVATION ⚙️ Scalable Efficiency AI enables organizations to operate at a new scale — automating tasks, streamlining decisions, and amplifying productivity. This isn’t just about cost-cutting and efficiency — it’s augmenting talent for higher-value work and building systems that continuously learn and improve. 🎁 Enhanced Value Propositions AI enhances what you offer — and how it’s experienced. From smart, adaptive products to deeply personalized services, it allows you to deliver more relevance, utility, and meaning to every customer. The frontier of value lies in customer responsiveness and learning at scale. 💞 Shifting Customer Relationships AI transforms how we engage with customers — not just improving service, but enabling co-creation, building trust, and responding to individual needs in real time. The most successful companies will be those that become embedded in customers’ lives through intelligent, trusted relationships. 🏗️ Redesigning Organizations Organizations must evolve from static hierarchies to adaptive systems that blend human and AI capabilities. This means rethinking workflows, decision-making, and structures to be more fluid, responsive, and innovation-driven. AI is not a bolt-on — it enables dramatic reconfiguration of value creation. 🧑💻 The AI Agent Economy AI agents are becoming participants in the economy — acting on behalf of users, negotiating, coordinating, and executing tasks. This shift calls for new strategies, where businesses design for agents as well as humans, and where trust and interoperability become core to competitive advantage. 🌐 AI in Platforms and Ecosystems The most powerful business models today are built around data-rich ecosystems. AI turns data into action, unlocking new platform value and shared innovation. Success increasingly depends on how well you participate in — or build — dynamic, intelligent ecosystems. CAPABILITIES 🚀 Capabilities for AI Evolution Thriving in this landscape requires more than tools. It demands vision, adaptability, experimentation, and the ability to work across boundaries — human, organizational, and technical. These capabilities are the foundation of tomorrow's business models and success.

Monetizing AI in Manufacturing: From Cost Savings to New Revenue Streams AI in manufacturing isn’t just about efficiency—it’s about unlocking entirely new business models. Forward-thinking manufacturers are moving beyond cost reduction and leveraging AI to generate revenue in innovative ways. Here’s how: ✅ Cost-Saving Models - Predictive Maintenance: PepsiCo’s Frito-Lay plants added 4,000 production hours by predicting failures before they happen. - Quality Control: LG Electronics uses Azure Machine Learning for predictive defect detection in smart factories.  - Energy Optimization: Siemens gas turbines use AI to adjust fuel valves and minimize emissions - Digital Twins: Siemens optimizes turbine performance and reduces emissions using AI-driven virtual replicas. ✅ Revenue-Generating Models - Data-as-a-Service: Georgia-Pacific monetizes anonymized sensor data for supply chain insights. - Platform Ecosystems: Siemens MindSphere creates an IoT and AI-driven ecosystem for predictive analytics and industrial automation - Pay-Per-Use: BASF shifted from selling automotive paint by volume to charging per painted car, leveraging AI for optimized paint application - Smart Products: Siemens embeds AI into automation systems, creating premium offerings. Why does this matter? AI is transforming manufacturers from product sellers into solution providers, creating recurring revenue streams and deeper customer relationships. 💡 Question for you: Which AI-driven business model do you think will dominate manufacturing in the next 5 years—Data-as-a-Service, Outcome-Based Pricing, or Smart Products? #AI #Manufacturing #industry40

Most AI today is like an overenthusiastic intern. It suggests ideas, flags issues, and predicts trends—but when it comes to actually getting things done, it politely waits for human approval. That is about to change. There are two types of AI in business today: 🔹 Probabilistic AI that brainstorms, forecasts, and recommends 🔹 Deterministic AI that automates, executes, and completes tasks Most companies focus on the first while ignoring the second. It is like hiring a chef who only writes recipes but never cooks the meal. Some businesses are already shifting. A telecom company where AI diagnoses network issues and fixes them before customers notice A hospital where AI coordinates patient care without waiting for endless approvals A bank where AI detects fraud and takes action in real time instead of just sending alerts In the next two years, businesses will fall into one of two groups. ✅ Those using AI to run their operations with speed and precision ❌ Those using AI to make suggestions that still require manual follow-ups One of these groups will move faster, serve customers better, and build more efficient teams. The other will wonder why their AI investments are not translating into impact. The real question is not whether your company has AI. It is whether AI can take action without waiting for human hands to push the final button. What do you think? Please share your thoughts on this subject. https://lnkd.in/gDvgR3u2 #ArtificialIntelligence #BusinessTransformation #AgenticAI #FutureOfWork #Automation

AI Agents and the Future of Business: The Real Shift in Value Creation For years, LLMs have dominated AI discussions, but the real shift is happening with AI agents—autonomous systems that drive real economic value. Maximilian Vogel's latest article breaks down why agency, not just intelligence, will define AI’s impact. The Economics of AI Agency -AI Agents Will Reshape Business Models – Operating income, cash flow, and efficiency will be re-engineered, not just improved. -Capital Efficiency at Scale – AI agents will reduce costs and unlock new revenue streams. -AI-Driven Market Expansion – The real ROI comes from transaction efficiencies and new business models. -From Software to AI Platforms – AI will automate entire workflows, redefining how businesses operate. -Skate Where the Puck Is Going – Companies focused on optimizing old processes with LLMs will miss the real transformation. Why This Matters Now Businesses that don’t adapt won’t just lag—they’ll become obsolete. Starbucks evolved beyond coffee into a software-driven logistics company. The next market leaders will be AI-powered platforms, whether they plan for it or not. If you’re not paying attention to AI’s trajectory, you’re already falling behind.

A Surge of Value Creation is About to Transform Everything – Are You Ready? AI is about to change everything (again). OpenAI’s latest research proves that large reasoning models (LRMs) trained with reinforcement learning are not just automating tasks—they are outperforming human-crafted problem-solving strategies at an elite level. What does this mean for business leaders, especially in healthcare and private equity? 🔹 AI is evolving beyond automation—it can now reason, adapt, and make strategic decisions, redefining how organizations operate. 🔹 Complex problem-solving is no longer exclusive to humans—AI is now competing at the highest levels of logic, coding, and decision-making. 🔹 General AI models are surpassing specialized systems, meaning scalable, adaptable AI will drive the next wave of transformation in every industry, including healthcare. For healthcare leaders, this signals a seismic shift—AI will redefine diagnostics, patient engagement, operations, and financial modeling. We are entering an era where AI doesn’t just assist—it thinks. For private equity leaders, this is a watershed moment. AI-driven operational efficiency, smarter patient acquisition, and predictive analytics will dramatically impact healthcare portfolio performance, EBITDA expansion, and investment strategies. The firms that integrate AI into their playbooks will unlock unprecedented value—those that don’t risk being left behind. Humanity is getting an upgrade that we can’t even begin to fathom. For those who want to dive deeper, I’m attaching OpenAI’s research paper here—this is a fascinating look at the future that is unfolding before our eyes. The question is: Is your organization prepared to ride this wave, or will it be left behind? Let’s discuss—where do you see AI making the biggest impact in healthcare and healthcare private equity over the next 3-5 years?