Durable Growth: How Lean Can Fulfill Generative AI's Potential

Most people overestimate the value of Generative AI in the short term and underestimate its long-term potential. Why? Because many companies are still looking at Generative AI and LLMs as a solution in the hunt for a problem.

That approach typically results in a cycle of inconclusive Proofs of Concept (POCs) and stalled pilot projects. No matter what you've read, simply using ChatGPT is not enough. AI-leading companies know that the performance of AI models will only increase, meaning those companies who don’t start capturing value soon, will be left behind.

AI leaders know the intelligent path forward (where real value will be captured) is to find tangible problems worth solving. That’s where the Lean methodology comes into play.

Core Principles of the Lean Methodology:

The Lean Methodology has long been cast as a tool for operational efficiency, but it also holds a tremendous opportunity to accelerate growth. At its core, Lean is about delivering maximum value to the customer while minimizing waste. It's about aligning every facet of an organization—from product development to customer service—to that value-creation mindset for customers. The essence of Lean lies not just in doing things efficiently but in doing the right things.

1. Customer-Centricity: At its heart, Lean is about understanding what the customer values. This principle requires businesses to step into their customers' shoes and understand their needs, desires, and pain points.
2. Value Stream Mapping: Once the value is defined, the next step is to map out every process contributing to delivering that value. This mapping helps identify non-value-adding steps, which can be eliminated or optimized.
3. Flow: Lean emphasizes the importance of uninterrupted flow in processes. Any friction or bottleneck can lead to delays, penalties, and limit your ability to capture market-competitive pricing.
4. Pull: Instead of pushing products or services onto customers, Lean promotes a pull system. This means producing (and marketing) only what the customer wants. This helps avoid overproduction (e.g., features they don’t use), and ensures optimal product-demand fit.
5. Continuous Improvement: Lean is not a one-time initiative but a continuous journey. Organizations should always be on the lookout for ways to improve processes, reduce waste, and enhance value delivery.

Leveraging Lean Principles with Generative AI for Value Creation:

Using the Lean ‘lens,’ we can identify use cases where Generative AI can resolve common business problems and help drive top-line growth.

1.????Personalized Value Propositions: Generative AI enables 10x the speed of asset (e.g., ad taglines, images, site design) creation. By combining that trove of content with advanced data analytics, brands can now target specific demographics with unprecedented precision (n=1), crafting experiences that are not just tailored but bespoke ( Persado ).

The result? Businesses are perceived not just as providers but as attentive partners in the consumer journey, maximizing engagement and product stickiness.

2.????Optimizing the Value Stream: Generative AI can eliminate non-value work, streamlining complex projects like building design (augmenta.ai) to reduce uncertainty and increase earnings. Or it can augment the highly complex world of healthcare by using LLMs to improve health outcomes, optimize billing, and enhance risk stratification ( Hippocratic AI ). Or, by leveraging the power of Variational Auto Encoders (VAEs) and anomaly detection models, organizations can proactively identify and rectify defects ( Diffblue ) and bugs to reduce the risk of costly downtime and rework, which limits earning potential.

By preemptively addressing inefficiencies, Generative AI ensures each touch-point with a customer or user is positive and a ?value-add.

3.????Automating Value Flow: Generative AI can make real-time decisions based on vast amounts of data. Sales support requires tedious administrative work, routine client interactions, and leadership time to manage forecasting. AI can accelerate these tasks, ensuring that the flow of value delivery remains uninterrupted. For example, applying Large Language Models (LLMs) can automate your sales prospecting by combining multiple data sets to find your ideal customer and send personalized AI-powered messages ( Clay ). Or you can massively scale your sales coverage by creating hyper-personalized videos to improve engagement and loyalty ( Tavus ).

4.????Demand-Driven Production and Services: Generative AI can help product teams and supply team leaders accurately forecast customer demand. This predictive power ensures that businesses produce only what is needed, adhering to the pull principle of Lean. Similarly, companies who have struggled to get insights into buying trends because of data siloes will soon be able to use natural language to query across warehouses and lakehouses to gain insights that improve decisions ( Microsoft Fabric Community ).

5.????Iterative Learning and Improvement:

One of the most potent aspects of AI is its ability to learn and improve over time. By continuously analyzing outcomes, feedback, and new data, AI models can be refined, leading to better results. This aligns perfectly with the Kaizen principle of continuous improvement.

Generative AI leaders understand that deploying an LLM-based solution is just the beginning of creating value. Luckily, there’s a whole new world of AI-enabling capabilities that allow companies to continue deploying new versions of their models while also ensuring the underlying data is reliable ( Cleanlab ) and the models are trustworthy ( WhyLabs ).

The Take Away

Marc Cuban recently said, "There are two types of companies in the world: Those who are great at AI and everybody else." If you believe that's true and hope to stave off the next wave of creative disruption, there’s no time to wait. But... you also can’t waste cycles on AI projects that don’t move the needle. Take inspiration from Lean and focus on enhancing customer value. Leverage AI's predictive and generative capabilities to improve efficiency, automate decisions, and deliver durable growth for years to come.