Leveraging Generative AI for Growth Strategy: Immediate Applications and Benefits

Understanding Generative AI in Strategy Work

Generative AI is revolutionizing the field of strategy work, offering unprecedented speed and production improvements. It can accelerate strategy and M&A decisions, enhance the quality of inputs into those decisions, and increase the quantity of decisions receiving proper research support—all at a reduced cost.

What is Generative AI?

Generative AI relies on deep learning models to understand written text requests and produce outputs from vast datasets, such as a snapshot of all data on the internet. It's essentially a highly complex data search and organizational tool that sifts through text, images, video, and more to serve up the user's request.

Limitations of Generative AI

Despite its power, it's crucial to recognize Gen AI's limitations:

• It cannot analyze content and develop insights independently.

• It struggles with mathematical tasks and can't develop or run analytical models.

• While it has access to vast quantities of information, it needs guidance on how to use that information effectively.

In essence, Gen AI can't simply hand you the answer to your market analysis question or produce insights from a single prompt. However, by understanding its strengths and limitations, we can leverage its capabilities to create significant value in strategy work.

The 5 Phases of Growth Strategy Work

Growth strategy work typically encompasses five phases:

1. Scope Definition

Defining the decisions that need to be made and the questions we need to answer.

2. Foundational Research

Surfacing the information we need to inform our strategy.

3. Insights Development

Turning the collected information into actionable insights.

4. Options Development

Identifying potential routes with pros and cons for each.

5. Decision and Execution Roadmap

Choosing the best option and planning its implementation.

It's important to note that Gen AI is not equally suited to assist with all these phases. At the present level of development, it excels primarily in the foundational research phase, although it could play a significant role in the other phases as well if guided by an experienced human.

How Generative AI Transforms Foundational Research

Traditional Challenges in Research

Organic and inorganic growth work usually requires developing up-to-date insights on customers, competitors, products/services, and technology, often in spaces relatively new to the company. Traditionally, this involves:

• Purchasing expensive syndicated reports ($5k-$10k) that often provide only general overviews.

• Investing weeks of expensive talent in searching for and reading articles, websites, 10-Ks, etc.

• Spending additional time organizing, vetting, and curating the collected information.

Generative AI's Role in Research Acceleration

With the right Gen AI agents, we can produce a more complete and robust set of on-target research in a couple of days than a strategy team can produce in weeks. This research can be summarized for expert review in a standard format, quickly surfacing the growth strategy research we need.

Types of Information GenAI Can Provide

In our experience, GenAI can assist in gathering and organizing information on:

• Market sizing

• Market trends and innovations

• Product/service segments and sizing

• Customer segments and sizing

• Competitor segments and profiles

• Competitive dynamics, including provider-switching decisions

• Risks and threats

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Overcoming Challenges in Implementing GenAI for Strategy

Need for Specialized AI Agents

Standard large language models aren't set up to address this sort of research effort out of the box. One needs an AI agent that has been properly prompt engineered, over many similar requests, to know what sort of information we need, from what sources, and how to present it. In addition there are add on tools that are necessary, such as the ability to use web searches as context for the RAG (Research Assisted Generation), which is not standard on all LLMs.

Importance of AI Agent Chains

To get the desired research results, multiple AI agents are needed, each handling a discrete part of the research question and often passing its output to another agent to build upon. One agent that has been built and tested on the market scan process can be paired with another that has the ability to quickly research competitors, for example. Experience and expertise in deploying the right agent at the right time is at the heart of what is required to do GenAI-assisted growth strategy work well.

Role of Human Experts in the Process

A growth strategy expert is still crucial to review the AI output, rerun AI work as needed, identify new questions based on early research, and develop preliminary insights. Understanding nuances in the research requires an expert with years of experience to parse the market scan information into the right format for a client. Digesting results from GenAI research can feel a little like drinking from a firehose. An experienced growth strategy expert with the ability to separate the wheat from the chaff is critical.

The Competitive Advantage of AI-Powered Strategy

Organizations that figure out how to leverage Gen AI will drive faster, better-informed decisions, resulting in a distinct and powerful competitive advantage. This advantage comes from:

• Speed and efficiency gains in research and analysis

• Improved decision quality due to more comprehensive information

• Cost reduction and increased research capacity

  
  

Case Study: Chronos Insights' AI-Powered Process

At Chronos Insights, our consultant-led, AI-powered process can produce robust, reviewed, and curated research on various topics in a single week—a task that traditionally takes a month or longer.

Conclusion: Embracing Change for Strategic Advantage

Change is coming to the world of strategy. Organizations that embrace and effectively implement Generative AI in their growth strategy work will be well-positioned to outperform their competitors. By leveraging AI to handle time-consuming foundational research, strategy teams can focus their expertise on developing insights, options, and making critical decisions.

Are you ready to leverage Generative AI for your growth strategy? Consider how AI-powered, consultant-led research could transform your decision-making process and drive your competitive advantage.