Demystifying What to Do with AI.

As with all your best decisions: start with your customers

We are reaching DEFCON 5 in the current AI hype cycle. The signal-to-noise ratio is so dialed up that it might require a neural network to decipher it all. But don’t get too caught up in it. From our research and development here at DCG ONE, some of it is warranted and some not so much. Make no mistake, this is not an NFT scam or a new crypto play. There is real value to be extracted if you lean in with discipline and a customer-centric approach.

We have been down this road before with new technologies over the last three decades, and for all the whiz-bang that’s available, the opportunities always come from the same place: How can we use this technology to add value for our customers?

With that singular question, you can now take many different approaches. For example, streamlining a task that shortens delivery time might be an obvious choice. Starting with shortening the delivery time and working backwards will allow you to realize other benefits in the process, but most importantly, it will allow you to focus on use cases and processes that benefit your customers the most. That, in turn, will be the catalyst in leveraging these exciting capabilities to create the most positive impact on your business.

Brad Clarke, President and CEO of DCG ONE, is extremely bullish on building AI capabilities that drive business change. “We are working hard to invent new services via AI to support our customers. The trick is understanding where the technology provides the deepest value to our customers, testing, iterating, and continuing to develop a culture of learning around how these tools can support their evolving needs while serving as a catalyst for growth in our own business.”

But your customers may need more

Applying good change management, and solid customer-centric use cases will provide you with the building blocks for jump-starting your efforts in AI, but is that all there is?

“This technology brings so much opportunity in how we will be able to read and understand vast amounts of data.” said Andy Lueck, DCG ONE SVP of Experience. “Looking at your assets and capabilities will allow you to expand further and create new products and offerings that are built on the foundation of AI and data. But it will take diligent work to understand what you are providing the large language models (LLMs) and how that will translate into customer value in the short and long term. Working in a product framework to develop your offers will provide the structure you need to properly create new contribution areas to your business. The team here at DCG ONE are working on exactly that, setting up ourselves and our customers to take the next step into this new world, with less hype and more value.”

Getting started is always the most difficult step, but simplifying your approach will make creating your opportunities more tangible. Here is a quick list of things to do to make sure you are engineering for success as you go:

1. Get leadership on board. As we are seeing with our own efforts here at DCG ONE, having the leadership team not only on board, but highly engaged and part of the steering team will provide the head nods from prospective team members you will need to get others on board.

2. Cast a wide net for expertise. Involve team members that live outside the technology. Walk through the potential capabilities and ask “What are our customers asking for? How would you use this to solve those customer problems if it were available? What would you do first?” Great ideas will come from unexpected places.

3. Develop simple use cases and iterate. Know what data you need, what data you own, and what data you need to find. Establish how each use case adds value. Be iterative but don’t take too much time introspectively. Once you have the outline of a use case, run it past leadership, the team, and your customers to see how it might evolve.

4. Check yourself before you wreck yourself. Make sure that the data you are planning to use is ok to use for this purpose. Red flags should come up around personally identifiable information (PII), personal health information (PII), and corporate secrets. You will be able to mitigate risks in how you build things but steer clear of putting your company or customer data within the publicly available tools. Our technology team can help.

5. Plan and build. Remember to keep the first use cases simple so that you can be in production quickly and honing your expertise.

6. Bring in partners. You can’t know everything, so engage with partners that can help you move forward.

Discipline will be key in separating the hype from the noise, so stay strong. Keep it simple to start, get your leadership on board, and ask for help. From there the possibilities are limitless.

If you would like to explore how AI can impact your business, please reach out and let us know if you’d be interested in a lunch-and-learn session on this topic.

[email protected]