AI Catalyst Partner Matthew Simons shares practical steps on how to overcome AI adoption challenges and set the stage for successful implementation with a powerful AI vision and strong foundations.
In our previous posts, we introduced the AI Strategy Canvas and explored crafting an AI vision. In this post, we will focus on a critical component of your AI strategy: identifying and prioritising AI initiatives specifically for sales, marketing, and operations. We'll also demonstrate how to use AI as a co-pilot in this process, showcasing the power of AI even in strategic planning.
AI initiatives in these areas are specific projects or use cases where AI can solve business problems or create new opportunities. For many organisations, these could range from AI-powered lead scoring in sales to personalised marketing campaigns, or predictive maintenance in operations. The key is to identify initiatives that align with your business strategy and can deliver measurable value.
The traditional approach to identifying use cases is to hold numerous conversations with the relevant stakeholders within the domains in scope and go through a series of questions around your core business processes to bottom out problems you want to solve or opportunities that can be opened up with AI.
In this blog, we want to encourage you to leveraging AI tools like Open AI's GPT-4, Anthropic's Claude, or custom AI models to assist you in brainstorming potential AI initiatives. When using Generative AI, it's crucial to provide the relevant context, set the right tone, and give examples to get the most relevant and useful responses.
Here is a basic 4-step framework to help you craft an effective AI prompt.
An example of a well-crafted prompt using the above mentioned 4 steps looks something like this:
"As a B2B software company with 50 employees and £5 million in annual revenue, we're looking to improve our sales efficiency. Our main challenges are lead qualification and sales forecasting. Generate a list of 5 potential AI initiatives to address these challenges. Use a professional tone and format each initiative with a title and brief description. Here's an example:
AI-Powered Lead Scoring: Implement a machine learning model that analyses historical data to automatically score and prioritise leads based on their likelihood to convert."
Note: For models like ChatGPT custom GPTs or Claude projects, you have the ability to add more specific company information to enhance the relevance of the AI's responses. However, always prioritise data privacy and security when considering what information to include.
Let's explore potential AI initiatives across sales, marketing, and operations, using AI as our co-pilot:
AI prompt: "As a sales manager in a B2B software company targeting mid-size enterprises, suggest 3 innovative ways AI can improve our sales process. Focus on challenges like long sales cycles and complex decision-making processes. Provide a title and brief description for each suggestion."
AI prompt: "As a marketing director in a resource-constrained SME selling productivity software, propose 3 AI applications that could enhance our marketing effectiveness. Consider challenges like limited budget and difficulty in personalisation at scale. Format each suggestion with a title and concise explanation."
AI prompt: "As an operations manager in a growing SaaS company with 100 employees, recommend 3 AI applications that can streamline our operations. Address issues such as scaling customer support and optimising resource allocation. Present each idea with a clear title and short description."
Start with human-generated "What If" questions:
Then, use AI to expand on these ideas:
AI prompt: "As a strategic consultant to a B2B software company, expand on the provided 'What If' scenarios. Generate 5 more innovative 'What If' questions related to AI applications in sales, marketing, and operations. Consider our company's focus on improving efficiency and customer experience. Format each question with a brief explanation of its potential impact."
Discuss and refine the AI-generated ideas with your team.
Once you have a list of potential initiatives, you need to evaluate them for both business value and technical feasibility. Traditionally, we will do an in-depth assessment into forecasting the potential value generated from the initiative whether in terms of cost savings, revenue generation or even specific improved efficiencies. We will also work with our more technical peers to under the feasibility of implementing these AI initiatives from different perspectives such as data quality and availability, infrastructure and expertise to support it, and the level of business change required to implement them effectively.
We still believe that the traditional approach is still the most comprehensive and accurate way to get a comprehensive assessment. However, you can also use Generative AI to give you some early indicators about their value, feasibility and complexity:
AI prompt: "As a business analyst in our B2B software company, assess the following AI initiatives [list your initiatives]. Provide a brief evaluation of potential value and implementation feasibility for each. Use a scale of 1-5 for each factor, where 1 is lowest and 5 is highest. Consider our company size (50 employees), budget constraints, and current technology stack. Format your response in a table with columns for Initiative, Value Score, Feasibility Score, and Brief Justification."
Note that this example prompt misses out on several details such as your current technology stack, state of your infrastructure and internal knowledge of your business. Generative AI is capable of taking all the contextual information as part of a bigger prompt or series of prompts as well.
With your initiatives now scored by both value and feasibility, use a 2 x 2 prioritisation matrix as described earlier. You can even use AI to help plot your initiatives:
AI prompt: "As a project manager in our B2B software company, categorise these AI initiatives based on their value and feasibility scores. Group them into four groups: Quick Wins, Long-term Investments, Fill-Ins, and Time Sinks. Consider our company's current AI maturity level and resource constraints. Present your categorisation in a clear, bullet-point format with a brief explanation for each categorisation."
For your prioritised initiatives, use AI to help develop initial action plans:
AI prompt: "As a programme manager in our B2B software company, generate a high-level action plan for the AI initiative [specify initiative]. Include objectives, required resources, timeline, potential risks, and key stakeholders. Consider our company size, current technical capabilities, and the need for quick wins to build AI momentum. Format your response as a structured plan with clear headings and bullet points for each section."
By using AI as a co-pilot in this process, you can generate more diverse ideas, gain initial assessments quickly, and create draft plans efficiently. However, remember that AI is a tool to augment, not replace, human decision-making. Your team's expertise and understanding of your unique business context remain crucial.
As you implement AI projects and learn from them, regularly revisit your list of initiatives. Your priorities may shift as your AI maturity grows and new opportunities emerge in sales, marketing, and operations.
Ready to start identifying and prioritising your AI initiatives with the help of AI? Download our AI Strategy Canvas AI Strategy Canvas today and use it, along with AI assistance, to map out your AI opportunities in sales, marketing, and operations!
In our next post of this series, we'll explore how to assess your AI readiness and how to ensure that you have the capabilities you need to succeed in implementing AI initiatives.