Generative AI technology is currently making advances at breakneck speed towards a vision that promises to transform our world and our lives. Established organizations that are based on mature business models and stable operations regard generative AI on a range between a potential disruptor that might eventually eliminate their right to exist in their current form (SW development firms or legal firms) and a blessing that could take their performance outcomes to the next level (imagine what generative-AI can do for customer service or the entertainment industry).
Just like any new world-changing technology, CIOs, CTOs and managers of P&L units are looking for ways of leveraging it to gain an edge over the competition. At the same time, new technology introduces significant challenges and thus, resistance arising from the organization’s safeguard functions (IT security, data privacy, etc.). Similarly to when cloud technology was introduced to the world, I expect we’re going to see an attempt by the functions responsible for standards & policy, to enforce clear restrictions while trying to provide as good an access as possible to the technology for internal stakeholders. At the same time, we can expect to see local initiatives in areas of the organization where the rubber meets the road which is where its potential value is most appreciated and needed. This internal tension between standards and business needs is a natural dynamic for any new groundbreaking technologies and generative AI is no exception.
Unfortunately, when trying to do the right thing, organizations tend to be slow in adopting new technologies using the standard top-down approach and letting business units take the reins results in islands with different approaches that become a nightmare for IT later on.
At Spyre, we help organizations get to technology-based business value faster by applying an entrepreneurial approach and thus applying accelerator techniques to technology-based ventures. Instead of looking at this solely through the lens of a top-down approach or a bottom-up opportunistic approach, we recommend combining the two. Following are three counterintuitive principles that we apply with our clients for great results in the form of successful technology deployments. They are not commonplace in established organizations and are based on principles of success exhibited by thriving innovation ecosystems.
Start with value instead of platform - Instead of strategizing about infrastructure so that you can later on have the ultimate internal offering, start with the value that generative AI can create for you. The Spyre approach is to recruit your employees as innovation leaders and have them investigate numerous opportunities for extracting business value out of technologies such as generative AI. This aims to harness the strong support of BU leaders since they can see exactly what the technology can do for them. This approach regards your employees as entrepreneurs and the executives as investors. At the same time, such an approach allows IT to plan on just enough infrastructure that can support the most valuable opportunities that are being evaluated.
Test a lot of educated guesses instead of making a few big bets - The natural tendency of organizations is to look for the ultimate homerun and build a groundbreaking project based on the new technology at great effort and expense. The nature of an accelerator is that it tests a lot of business value propositions in a cost-effective, sustainable manner. We can do the same here regarding every AI-related opportunity as an educated guess, limiting the time and resources required to test it and engaging decision makers to participate in the selection and investment decisions. Thus, we can actually mitigate the overall risk while maximizing the potential reward.
Connect the organization’s experts to foster learning and success - It is not enough to rely on AI experts in order to successfully deploy opportunities that affect business outcomes. We must engage internal experts who are familiar with legacy systems, existing practices, customer preferences, etc. This insight comes from thriving startup ecosystems where it is clear that being connected to networks of knowledge is key to a venture’s success. As AI-related opportunities are being evaluated, we have to connect the teams driving them to the existing network of internal experts. Innovation is an extreme team sport and the successful utilization of anything new such as generative AI must be done in cooperation with the existing team.
In summary, by adopting best practices from the world of accelerators, we can actually accelerate our way to successful deployments of generative AI technology for the benefit of our organization in the form of improved KPIs such as increased revenues, improved operational efficiencies, and customer satisfaction.
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