Artificial Intelligence Reaches a Permanent Level on the Gartner Hype Cycle
In the world of technology, a new era is upon us - the era of Artificial Intelligence (AI). This revolutionary technology has taken the global stage by storm, transforming various industries, creating millions of jobs, and sparking intense competition among nations.
The venture capitalists find themselves in a unique predicament. The fear of missing out on AI could potentially mean the end of their careers, leading to a general consensus that overpaying is better than missing out. The due diligence process, traditionally a crucial step in investment, is proving to be too slow in the fast-paced AI landscape. As a result, hype investments have become necessary.
AI's financial model is one of continuous growth and acceleration. Investments in AI lead to valuation inflation, revenue growth exceeding projections, and a market that is growing daily. This growth is driven by the compounding improvements in AI, where better data leads to better models, better models lead to better applications, and better applications lead to better data.
The future of AI is not without its uncertainties. Scenarios ranging from the infinite peak, the catastrophic collapse, to transcendence are all possibilities. However, one thing is certain - AI has broken the Gartner Hype Cycle model, which predicted technology adoption for 30 years. We have entered the post-cycle era: permanent maximum hype sustained by permanent maximum change.
The attention economy plays a significant role in AI's perpetual hype. Modern technology requires constant attention, viral moments, narrative momentum, and FOMO generation, all of which AI delivers continuously. As a result, no one can afford to be disillusioned with AI. Companies must adopt or die, countries must compete or fall behind, individuals must use or become obsolete, and skeptics get eliminated.
In this post-cycle world, organizations should focus on continuous adaptation, permanent learning, flexible architecture, scenario planning, and resilience over efficiency. Individuals, on the other hand, should surf the waves of change rather than fighting them, engage in meta-learning, have a portfolio approach, build human connections, and manage permanent change stress.
AI's speed prevents disillusionment. Problems are fixed before widely recognized, limitations are overcome quickly, new capabilities distract from failures, and competition drives improvement. AI has a viral adoption strategy, with every breakthrough going viral, immediate global access, built into everything, and mandatory adoption becoming a competitive requirement.
The baseline for AI capabilities constantly shifts. In 2022, AI was able to write, in 2023 it could code, and by 2024, it may be able to reason. By 2025, AI could potentially do everything. This rapid evolution and boundless use cases prevent the trough of disillusionment.
AI has already shown its utility and applicability across various industries, job functions, and problems. Unlike previous hype cycles, AI actually works for many tasks, providing measurable productivity gains, real cost savings, and immediate applicability. The universal adoption of AI creates pressure for individuals, companies, industries, and society to adapt to AI.
The news cycle for AI includes headlines, viral videos, thought pieces, panic articles, and media cannot afford to ignore AI news. Examples such as the launch of ChatGPT in November 2022 and its continued high hype levels as of May 2023 demonstrate AI's perpetual peak. Instead of the traditional pattern of the Gartner Hype Cycle, AI is experiencing a permanent plateau at maximum hype, where every new capability prevents the crash that should come.
In conclusion, the AI revolution is here, and it's here to stay. The cycle is dead because the future arrived before the present could disappoint. As we navigate this new era, it is crucial for individuals, companies, and societies to adapt, learn, and embrace AI for a prosperous future.
