InnerVentures

In this post I’ve tried to elicit some insights using a Question and Answer approach with Copilot around best approaches to AI transformation. All still in service of the new trend report I’m working on. Some interesting observations – all of Copilot responses are in grey background. My commentary is in blue background. I only took one round of answers in both cases wanting to test efficacy at this level.

Question:

Can you automate an AI transformation program with an adoption platform and if so what would that look like? Capture any companies that are doing so and the tools and steps they are following on their journey.

Answer:

Certainly! AI transformation involves integrating artificial intelligence (AI) into business operations, products, and services to drive innovation, efficiency, and growth. Here are the steps and tools commonly used in AI transformation:

1. Outline Your AI Strategy:
   • Define your business objectives and identify areas where AI can add value.
   • Execute pilot projects to gain momentum and demonstrate ROI¹.
   • Consider ethical implications and success criteria².
2. Build an In-House AI Transformation Team:
   • Assemble a cross-functional team with expertise in AI, data science, and business domains.
   • Provide broad AI training to employees¹.
3. Collect and Manage Data:
   • Data is crucial for AI. Ensure data quality, security, and compliance.
   • Use natural language processing (NLP) to process human language and extract insights from text or audio³.
4. Develop AI Models:
   • Leverage machine learning and deep learning models (e.g., computer vision, NLP).
   • Train and tune models to improve accuracy and performance over time.
5. Automate Workflows and Add AI to Applications:
   • Integrate AI into existing systems and automate manual tasks.
   • Use optical character recognition (OCR) for digitization efforts³.
6. Infuse AI Across the Enterprise:
   • Create a self-service portal for developers with standardized tools.
   • Use APIs to access data and existing app functionalities⁴.

Companies like IBM, McKinsey, and others have successfully implemented AI transformation. They emphasize strategy, data management, and cross-functional collaboration. Remember that AI transformation is an ongoing journey, requiring continuous updates and adaptation to stay competitive.

MY Commentary

What the above response misses:

1. Senior execs/leader engagement – a coalition to drive the transformation, not all execs, just a carefully select group of representatives
2. The end user or employee and the experience they currently enjoy (or don’t) and how that is supported and might have to change in support of the work they do alongside the incorporation of AI. Culture change also fits in here and needs to be considered.
3. A system or methodology for driving adoption with end users / employees. I wrote about this and a few other related items in this commentary recently: The role of Systems Culture and Strategy for AI adoption.
4. Technology’s role, for example SAP has just purchased WalkMe and appear to be aligning it towards supporting it’s customers on their transformation journeys: SAP has found a way to bring us all on the digital transformation journey | ITPro
5. A way to measure progress based on the KPI’s you’ve set. A good way to do that using Goal Mapping or OKR software and a roadmap view is outlined in this article I read recently: The secret to success: implementing an effective AI roadmap | TechRadar.
6. Learning systems. In other words, a way to determine current skillsets and future desired skillsets and then a way to enable everyone to upskill in achieving learning and skills goals.

Question:

What are the latest and best approaches to bringing design thinking and lean startup approaches to AI Transformation efforts and who is doing it successfully?

Answer:

Design Thinking and Lean Startup are powerful methodologies for driving successful AI transformation efforts. Let’s explore how they intersect:

1. Design Thinking:
   • Understand the customer and discover real needs.
   • Empathize with users, define problems, ideate solutions, prototype, and test iteratively.
   • Successful companies applying design thinking include IBM, Apple, and Procter & Gamble¹.
2. Lean Startup:
   • Evolve innovation using rapid experimentation and validated learning.
   • Build a minimum viable product (MVP), measure its impact, and iterate.
   • Notable Lean Startup success stories include Dropbox, Zappos, and Buffer².
3. Combining Both:
   • Use design thinking to understand user needs and ideate.
   • Apply Lean Startup principles to validate hypotheses and iterate on AI solutions.
   • Gartner estimates that over 50% of established corporations leverage Lean Startup techniques for business transformation³.
4. Top Economic Performers:
   • Companies that excel in digital transformation focus on strategy, talent, operating models, data, and scale adoption, not just technology⁴.
   • McKinsey emphasizes a holistic approach beyond tech, including design thinking and Lean Startup principles.

Remember, successful AI transformation involves a blend of methodologies, adaptability, and continuous learning.

MY Commentary

I really love this response, the combination of the two approaches is so well captured in point 3 and that’s exactly the benefit and advantage of each. There’s lots of overlap but the answer focuses on the differences and the strength of the two in combination. Love it.

Another thing I would say is that these approaches would cover what was missing from the first response, specifically point 3 of my commentary: A system or methodology for driving adoption with end users / employees. One similar to the approach I took here: Lean startup methodology applied to successful enterprise technology adoption

The final thing I would add is that these approaches, whether taken on their own or in combination, or whether in fact any other approach is taken (think Agile for example, just another variation of similar nature), must be taken seriously. It cannot be about putting lipstick on a pig, something faddish. It needs to be adopted wholeheartedly, embraced and the entire organisation needs to get behind it, for the long haul, not just a few months of a transformation program.