As Generative AI reaches the peak of the Gartner Hype Cycle, many organizations are currently deliberating among the three most likely positions, which are as follows:
- “We must take action now.”
- “Let’s observe the trajectory and evaluate our alternatives.”
- “I acknowledge the need for action, but what precisely should it be?”
If you fall into the first category, you have likely already identified the transformational prospects linked to engaging with a technique that generates efficiencies, enhances the effectiveness of actions, and evolves alongside your own knowledge and techniques. If this describes your situation, then innovation and transformation are on the horizon (*terms and conditions apply).
Within this category, as a pioneer, the industry is cheering you on and wanting it to work. People like me are keen to help make it a reality.
If you belong to the second category, you’re probably awaiting the outcomes of the first category’s endeavours. Alternatively, you might be considering updating certain work methodologies incrementally to gain some value as the technology matures and becomes more cost-effective. Even within this category, products like Microsoft Co-Pilot can offer significant benefits without necessitating a complete reimagining of your business operations.
However, if you find yourself in the final category, you might face a decision sooner than you anticipate. Some potential concerns could include:
- “My data isn’t prepared!”
- “We’ll be ready to explore AI in 18-24 months!”
- “The risks might outweigh the benefits!”
- “What should be our first step?”
- “Can we effectively unlock the value of our data? Will our team embrace it?”
- “How can we place trust in the results?”
For each of these queries, the solution is likely to be attempting to take action. In scenarios where we’ve aided clients on analogous journeys, we typically initiate with what is feasible. This involves crafting a journey map aligned with an enhanced experience, often in response to a current experience that might not be meeting the pace or promises of your organization.
One potential approach is to treat the new technology as a Product and keep it simpler. Some engagements we’ve done in this space are:
- Look for alignment to business strategy
- Establish AI/Data Governance to maintain the alignment to the strategy and govern the Product development.
- Run Change Management alongside the Product development. This can and should change the way people work (for the better) and needs to be managed as an outcome.
- Pilot an example off a small slice of data and process. Measure and scale the benefits.
Following this approach, benefits can emerge through a straightforward workshop or conversation that employs a tool or model that might not have existed just three months prior due to the rapid evolution of the AI landscape (more on this will be available in an upcoming blog post).
The risk tied to delaying or not embarking on the first step is that your competitors are probably already embracing it, or at the very least, an opportunity for innovation is being missed. The time required to achieve value is no longer comparable to that of a “conventional” development project. It doesn’t demand the same level of investment to gather and employ data to establish a connection (or pivot if it’s unsuccessful).
Regarding adoption, focusing on business outcomes empowers your organization and teams to concentrate on the value they contribute during the ideation phase. This approach invites effective governance into discussions because it captures these notions and encourages their growth and appropriate utilization.
In the realm of AI outcomes, after all is said and done, trust remains crucial – trust in the process, trust in decisions, trust in strategy, trust in data, and trust in people’s ability to employ automation as a means of enhancement and an elevated experience. If you can cultivate trust in the methodology and encourage the exploration of ideas, you might find yourself achieving even more remarkable outcomes than initially envisioned.
Start with the idea, focus on the benefits, build the trust through good governance and consider that the products used to bring Generative AI into the consciousness have only been freely available a short time and take the opportunity. We’d be glad to help!