Planning Your GenAI Journey

It seems like everyone these days is incorporating generative AI (GenAI) to improve efficiency, productivity, and costs. GenAI holds the promise to be a game changer, but many businesses aren’t sure whether or how it’s right for them. If you find yourself questioning whether AI is the right fit for your business, you’re not alone. Despite all the buzz, GenAI isn’t seeing universal adoption just yet. In fact, research by The Register finds that a whopping 81% of mid-market organizations are currently avoiding AI.1 They just don’t see the benefit.

While caution is understandable before jumping on the GenAI bandwagon (see our blog post about this), the pressure is mounting to harness GenAI and reap its benefits.

So, what’s the smart way forward?

In a word: planning. GenAI is a journey, and like any trip, it requires a roadmap and thoughtfully planned steps. Here’s some guidance for charting your course in GenAI.

Step 1: Set Realistic Expectations that Align with Your Business Goals

Embarking on the GenAI journey requires a clear vision and realistic expectations. What is your end goal or what problem are you trying to solve? Is it to save operating costs? Automate tasks to increase employee efficiency? Analyze customer data to discover new engagement models?

As you answer these questions, you must also manage expectations. Understand that GenAI, while a potent force, is not a silver bullet. Businesses should be realistic about what AI can and cannot do. You’ll need to define what success entails, the metrics for progress, and the problems you’re aiming to solve.

You should also make sure that your efforts align with your business objectives. Misalignment can lead to squandered resources and overlooked opportunities.

It’s also important at this first step to establish guidelines and policies that address security, privacy, and training so that data is being protected.

Step 2: Identify Target Workflows

A scattered GenAI implementation leads to frustration and subpar outcomes. You need to carefully consider your company’s workflows and identify those most likely to benefit from GenAI’s strengths from a business-case point of view. It’s also important to remember that GenAI doesn’t replace subject-matter experts (SMEs)—at least not yet. You should plan on having a human SME vet all of the work performed by GenAI. Here are some examples of what to look for in workflows that could make them good candidates for GenAI:

  • Team vs. individual workflows: While the hype around GenAI often spotlights individual achievements, companies work in teams, so it’s crucial to identify and target the team workflows that are well suited to AI.
  • Repetitive tasks: Tasks involving repetitive data processing are prime candidates for AI automation.
  • Data-driven decisions: AI can offer precise, timely insights for decisions that require data analysis.
  • Customer interactions: Businesses that have a high level of customer interaction can enhance customer experiences by integrating AI.
  • Large-scale operations: AI excels at handling tasks that are impossible for humans to accomplish in the same amount of time, making it ideal for large-scale applications.
  • Ideation and research: AI can help knowledge workers quickly hone their research questions and can generate ideas for content creators—headline options, social-media posts, SEO keywords, and more.

Step 3: Identify Technical Needs

When deploying GenAI applications, businesses often choose between two options: hosting large language models on a cloud infrastructure or accessing GenAI as a managed service. Both have some technical and cost considerations, including the following:

  • API access: Businesses will need to understand how to access and use the API provided by the AI model provider. This includes understanding the request/response format, handling errors, and managing API keys.
  • System integration: The AI model will need to be integrated with existing systems. This could involve writing custom code and setting up secure connections.
  • Scalability: While pre-trained models can handle many requests, businesses should consider how they will scale their usage as their needs grow. This might involve upgrading their API plan or optimizing their usage.
  • Cost management: Using a pre-trained model often involves ongoing costs, such as fees for API usage. Businesses should factor these costs into their budget.
  • Data security: You’ll need to ensure that data is sent and stored securely and that using the model complies with all relevant data privacy laws.
  • Maintenance: While businesses won’t need to maintain the AI model itself, they will need to manage the integration with their systems and keep up with any changes or updates from the AI model provider.

Start Your GenAI Journey with These Steps

The GenAI journey is not without its challenges, but with thoughtful planning and strategic implementation, it can lead to transformative outcomes for your business. By setting clear objectives and realistic expectations, aligning AI goals with business goals, identifying suitable workflows, and addressing technical requirements, your business can start incorporating GenAI with confidence.

To Learn More

Read more about AI in the following Prowess articles and reports:

To learn more about what we do at Prowess Consulting, view our latest research and follow us on LinkedIn.

1 The Register. “Top-tier IT talent doesn’t stick around in ‘mid-market’ organizations.” January 2024.

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