September 16, 2024 - With technological advancements, conversations around artificial intelligence (AI) are increasingly becoming a focal point for businesses looking to enhance productivity and efficiency. In particular, AI presents significant opportunities to optimize processes in CRM applications, such as those on Microsoft's Power Platform. However, while AI’s technical implementation is more accessible than ever, the real challenge lies in determining where AI can be most effectively integrated into business processes.

The real challenge: identifying AI's role in business processes

Implementing AI models in your CRM is not inherently difficult. For example, Microsoft's AI Builder offers a range of tools that make connecting AI models to your existing data almost as simple as plug-and-play. Whether configuring a document reader, setting up a custom model, or crafting a prompt, the process has been designed to be user-friendly. However, the ease of setup belies a more significant challenge: understanding where AI can add the most value in your workflow.

The crux of the issue is not the AI implementation itself but deciding where it makes the most sense to apply it. AI models excel at automating repetitive, low-risk tasks — the "noise" or "negative space" in a business process. These are the small, habitual decisions people make throughout their day that, while necessary, are often repetitive and offer little value when performed by a human.

Identifying the "noise"

In any CRM system, there are numerous micro-decisions that, while necessary, do not require deep human intervention. Examples include routine approvals, basic data checks, or low-level error corrections. These tasks are often performed on autopilot by employees, taking up valuable time that could be spent on more meaningful work.

Consider a scenario from a client in the dentistry field. Dentists see patients and submit notes for their office assistants to review. The assistants must then determine whether to archive the patient’s record, schedule a follow-up, or take further action. Often, these notes require a simple decision: archive the record if everything is in order. However, the assistants have to make this decision dozens of times a day, which is where AI can step in.

Implementing AI to manage the noise

Initially, the focus was on solving the more complex problems using AI, such as determining the necessity of follow-ups. However, it soon became clear that the real value was in automating the simpler, more repetitive decisions. By building an AI model to handle these routine tasks, a significant portion of the assistants’ workload was eliminated.

Using AI Builder, a prompt was created that effectively asked the AI, "Is this a routine approval, or does this require human intervention?" The AI would then process the dentist's notes and provide a binary ‘yes’ or ‘no’ answer along with a rationale. This output was displayed directly in the CRM, allowing the assistant to see the AI's decision and reasoning before making the final call. Over time, as the AI model was refined and trust was built, the process was automated entirely, freeing up the assistants to focus on more complex tasks.

The real benefit: freeing up human potential

The beauty of AI in this context is that even if only 80% of these routine decisions can be automated, the productivity gains are substantial. By removing the "noise" from a person’s daily tasks, AI allows them to focus on higher-value activities that genuinely require human insight and creativity. This not only improves efficiency but also job satisfaction, as employees are no longer bogged down by the mundane.

Conclusion: focus on the noise, not the core

When considering AI implementation in your CRM or any other business process, it is crucial to shift the focus from the core tasks to the noise that surrounds them. Identifying and automating these micro-decisions is where AI can truly shine, providing tangible benefits to workflows. The hardest part of implementing AI is finding these opportunities. Once identified, building and deploying AI models is a relatively straightforward process.

In summary, the key to successful AI integration lies not in the technology itself but in the ability to recognize the areas of the business that are ripe for automation. By focusing on the noise and leaving meaningful work to employees, AI can be leveraged to its fullest potential.

For additional information on how to leverage AI to automate tasks and simplify business processes, please reach out to the Digital Services Practice team to schedule a free consultation.