A deeper dive into the value of AI (part 1)

It only takes a moment to recognize the revolutionary value of AI, but everybody’s moment is different. The first time I saw a really effective machine learning (ML) model in action, I was thrilled. I am a stats guy from way back (the 1990s) and was excited to see patterns in data so quickly, not only descriptive patterns, but also predictive ones. I started looking at industrial applications in quality control but explored ones closer to home (specifically in quality and financial controls).

I was excited, but my real aha moment came with my second foray into generative AI. I tried ChatGPT very early on. It was fine, it was cool, but didn’t seem to deliver immediate value. About six months later, I read Geoff Wood’s book AI Leadership and tried out his approach of treating AI as a thought partner. I was stunned by the fresh perspective that I brought to my thinking, planning, and writing.

I have yet to lose my enthusiasm for AI. ?I do, however, need to articulate the possibilities for AI. Where can we really derive value? What are the potential aha moments for our organization to grasp the value of AI? In an earlier post, I articulated 4 different ways that AI can drive value for our organization – https://www.dhirubhai.net/pulse/youre-starting-use-ai-your-organization-how-you-know-its-adam-krob-jngbc/. The four sources of value in AI are

·?????? Easing simple tasks

·?????? Simplifying complex tasks

·?????? Acting as a thought partner

·?????? Becoming the interface

I want to go deeper into the first two in this post and the final two next week.

Easing simple tasks

The first source of value for AI is the most familiar – easing simple tasks. A lot of automated processes that leverage AI fit into this category. At first glance, this source of value is a pure margin play. If we can use an AI to reduce the time and human effort required to deliver core services, we will capture more profit. An example is a tool that does a first match of purchase orders, invoices, and bills of lading/delivery tickets.

There’s more value here, though. Easing simple tasks also has an impact on data quality. If we can automate tasks like data entry, we can reduce human input errors. Any situation where we are entering data more than once leads to double the chances of a keystroke mistake.? Finally, I also strongly believe that reducing the time spent on simple tasks gives everyone in the organization an opportunity to focus on higher value work, to train for new tasks, or to allow for enough slack to take on additional work (for example, handle a greater number of projects).

Simplifying complex tasks

The second source of value for AI has three different components. One example illustrates all three. One AI set of tools is well-entrenched in the construction industry – AI drive schedule review programs. How does it deliver value? First, it reduces the experience required to effectively review a schedule. This is a component of the scheduling process that requires significant knowledge and breadth of experience. Building best practices into an AI-based tool can enhance a new scheduler’s product. That doesn’t mean that the new scheduler doesn’t need to understand what a schedule reviewer tool flags as an issue, but it does mean that someone just starting out can benefit from a simple way to highlight potential issues. This leads to the second component of value – freeing team members to do higher value work. If flagging schedule issues automatically reduces the time it takes to review a schedule, the scheduler can spend more time working with the project team to adapt it to changes in the project or even issues highlighted by the AI tool.

The final component of value is the enhanced ability for an organization to implement well-known and highly valuable practices. In the area of scheduling, reducing the time and effort required to do schedule review can allow the scheduler/project manager to spend time bridging the gap between a traditional schedule using a tool like P6 and lean scheduling tools such as pull plans or TAKT schedules.

Looking beyond time savings

The value of technology tools is often expressed in time savings. For AI, we need to look beyond this simple notion of value to all the ways that AI can enhance our organization.