Tracking and Analysing AI Implementations: Why It's Crucial for AI Success

Your firm might be “using AI”, but if you don’t know how its being used, by whom and when, you're missing out on valuable insights and opportunities

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Generative AI (GenAI) is a relatively new player in the technology landscape, so we are all still trying to work out how to leverage its capabilities effectively. While the concept of AI is not new, its applications and implications are developing quickly, and each organisation—and indeed, each user within an organisation—approaches it differently. This personalised use of AI depends on various factors, primarily one’s job and role within the organisation, but also one’s personality and skill sets.

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The Personal Nature of AI Usage

How each person uses AI is unique, heavily influenced by their specific job functions, personality, and individual preferences. For instance, an accountant might use AI to streamline data entry and financial analysis, while a marketer might use it to craft personalised campaigns and analyse consumer behaviour. Personality and skill sets also play an essential role; some people are naturally more creative and inquisitive, which may lead them to explore innovative ways to use AI, while others may leverage their technical skills to optimise workflow efficiencies. Thus, the success of AI implementations relies significantly on user innovation.

To maximise the benefits of AI, it is crucial to teach individuals how to solve their unique problems using AI tools. Since everyone’s roles and thought processes are different, it's less about teaching them a one-size-fits-all method and more about empowering them to discover how AI can best serve their needs. This requires a focus on developing problem-solving skills with AI as a tool, rather than prescribing rigid methodologies.

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The Importance of Measuring AI Assistant Usage

Investing in any technology necessitates a thoughtful approach to tracking and measuring its usage. This is particularly true for AI assistants, whose usage needs to be meticulously tracked to gauge effectiveness and popularity. It's difficult to quantify the return on investment (ROI) for many AI platforms because the value they provide is often intangible and dispersed across various functions and individuals within an organisation. Therefore, the most concrete measure we currently have is the usage of these AI assistants.

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By tracking usage, we can derive a number of valuable insights:

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1. Overall Usage: Measuring the total messages or chats sent to AI assistants serves as a general indicator of the AI implementation's success. High usage rates suggest that the tool is valuable and beneficial to users.

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2. Assistant Popularity: Analysing which AI assistants get more use can reveal their popularity and effectiveness. This helps in understanding which features or approaches resonate most with users.

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3. Departmental Usage: Analysing usage data by department can reveal which divisions are adopting AI assistants successfully and which are struggling. This can inform targeted training interventions, ensuring all parts of the organisation are equally equipped to leverage AI.

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4. Individual Usage: Monitoring individual usage patterns can help identify users who may need extra training or support. Understanding what barriers exist for these individuals can lead to more effective training programs and increased overall adoption.

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5. Research Topics: By seeing the topics that users research with AI assistants, organisations can identify trends, common challenges, and areas where additional resources or solutions may be needed.

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6. Time of Usage: Analysing the time of day and day of week when AI assistants are most used can offer insights into work patterns and tool accessibility. This can help in scheduling training sessions and understanding peak times for support services.

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Strategic Decision-Making

All these insights are invaluable for strategic decision-making. Knowing which areas of the business are most engaged with AI allows for better resource allocation, targeted training, and informed marketing efforts. It also provides a clearer picture of how AI is driving value across the organisation.

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Our Proprietary AI Assistant Hub and Analytics Centre

At Propella, we have developed our own proprietary AI Assistant hub, known as "Sidekick". Sidekick includes a dedicated Analytics Centre (shown in the images above), that offers numerous benefits for its users. The Analytics Centre provides insights into overall usage, popularity, departmental and individual usage patterns, research topics, and utilisation trends over time, thus aligning closely with all the reasons highlighted in this article. If you are interested in learning more about Sidekick and the metrics it offers in the Analytics Centre, please reach out to us.

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Conclusion

While AI is still in its early stages, diligent tracking, measuring, and analysing AI assistant usage can provide crucial insights. These metrics not only reflect the current success of AI implementations but also guide future strategies to ensure that AI benefits are maximised across all sectors of the business. Through understanding and optimising how AI tools are used, organisations can better navigate the complexities of this powerful technology and achieve greater success.

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