GenAI: Navigating the Hype Cycle and Unveiling Potential Disruptions
Garrett Marshall
Revenue growth, digital transformation, and AI for growth companies focused on engineered wellbeing.
Are you wondering where AI stands in the hype cycle and whether it's worth your attention? Well, Gartner suggests GenAI has reached the "Peak of Inflated Expectations" and is entering the "Trough of Disillusionment".
What does that mean? Interest is dropping as implementations fall short. It's a pivotal time where you must be thoughtful and diligent-big AI investments today could be displaced by much better and 10x cheaper tech tomorrow.
But here's the catch: the other side of this coin is that the Trough of Disillusionment typically last 2 to 5 years before new technology accelerates and is broadly adopted by the mainstream.
When GenAI is implemented effectively, it becomes a competitive advantage, automating tasks, sparking innovation, and generating valuable insights. Moreover, sometimes these estimates are dramatically wrong and the missing the opportunity to capitalize on this game-changing technology could happen much sooner than 2 to 5 years.
So, the important question is how should your business be contemplating the implementation of AI? What can you do in the next two years to ride this wave?
??? Set a Clear Strategy
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Define a strategy that aligns with your business goals. Identify use cases, prioritize them based on impact and feasibility.
?? Educate (or at least inform) Everyone:
Educate your team and decision-makers about AI and how it can impact your business.
?? Data Action Plan
Figure out what data you need and how to make it accessible/actionable.
?? Skill Up
Hire or train your team to acquire the AI skills needed for development and deployment. If you don't do engineering in-house and you're the type of company that will buy not build AI, you probably still need someone in-house that oversees strategy (that's hard to outsource without being at the mercy of your partner/vendor).
GenAI feels further ahead to me than Gartner's estimates (and possess the inherent capability to improve exponentially). Where do you think it's at?
?? #AI #MachineLearning #FutureReady
HR Operations | Implementation of HRIS systems & Employee Onboarding | HR Policies | Exit Interviews
8 个月Well elaborated. "A prominent characteristic of the past industrial revolutions is the formation of boom-bust cycles. Even though inventions take substantial time to seep into society, the euphoria often leads inventors and investors to believe that their innovations will be quickly and widely adopted. This misconception is further perpetuated by think tanks, strategy companies, and the media, thereby creating hysteria. This hype often leads to an investment-pyramid scheme, thereby resulting in a bust when production exceeds demand enormously. However, these boom-bust cycles can be beneficial to society by providing the capital and workforce needed to build the infrastructure for the widespread adoption of new inventions. For example, the boom-bust cycles related to railroads, telegraph, and broadband communication infrastructures helped human society enormously. This pattern is already occurring in the Fourth Industrial Revolution with Metaverse, Autonomous Vehicles, and Quantum Computing. In fact, the current hype regarding AI may also lead to a partial bust, thereby leading to a third AI winter.
Founder and CEO @ SweatWorks | Product focused digital agency founder | Podcast Co-Host | Investor | Advisor
1 年Garrett Marshall I still think that we are in early days in adaptation. One of the biggest blockers has been the cost to implement at scale - however, complexity has been trended downwards.
25 Year Entrepreneur | Venture Partner | Advisor Building Companies in Health, Fitness & Tech. Harnessing Innovation and Entrepreneurship as a Luminous Force to Solve Industry Challenges. #GymJunkie
1 年Garrett Marshall I heard an interesting conversation that there is great traction with the suppliers to the Gen AI market and many Consumer companies finding growth but the Enterprise side has yet to find growth with B2B customers. The thesis is companies are reluctant to give up their data and considering in the build vs buy model to build but how is the question...
General Manager | Strategist | Entrepreneur | Ironman Athlete | Fitness Podcast Co-Host
1 年Feels about right. There will be some overuse that will fail along with consolidation that will occur before it gets to the other side.