Technology

AI Winter is coming? The Inevitable Tech Cycle: From IoT and Blockchain to AI

Mahmoud Darweash

24 Apr 2025 • 3 min read

As we approach 2026, the AI industry faces challenges reminiscent of past technological cycles. While major players invest heavily in AI, some startups may struggle to sustain operations, leading to potential market consolidations.

Lessons from IoT and Blockchain

IoT: The Promise and the Pitfalls

Between 2013 and 2016, the Internet of Things (IoT) sector experienced a significant surge, with venture capital investments increasing from $1.8 billion in 2013 to $3.44 billion in 2015 . However, many IoT projects faced challenges:

High Failure Rates: Studies indicate that approximately 74% of IoT projects are considered unsuccessful, often due to issues like integration complexities and unclear value propositions
Notable Failures:
- Hello (Sense): Despite raising significant funds for its sleep-tracking device, Hello shut down in 2017 due to lackluster sales and stiff competition.
- Revolv: Acquired by Google in 2014, Revolv's smart home hub was discontinued in 2016, leaving users without support.
- Basis Science: Bought by Intel in 2014, the company's fitness tracker faced safety issues, leading to its discontinuation in 2016.
- Staples Connect: Staples' attempt at a smart home platform was short-lived, ending in 2016 due to poor market adoption.
Success Story:
- Nest Labs: Founded in 2010 and acquired by Google in 2014 for $3.2 billion, Nest successfully integrated smart thermostats into mainstream markets, showcasing the potential of IoT when aligned with clear consumer needs.

Blockchain: Hype vs. Reality

The blockchain and cryptocurrency wave from 2017 to 2020 brought forth numerous startups:

Startup Proliferation: In 2018 alone, over 8,100 new blockchain companies were founded, marking the peak of blockchain startup activity during that period .
High Failure Rates: Approximately 95% of blockchain and cryptocurrency startups fail, often due to challenges like regulatory hurdles, lack of clear use cases, and market volatility .
Notable Failures:
- The DAO: An ambitious decentralized venture capital fund that collapsed in 2016 after a significant hack exploited vulnerabilities in its code.
- Iron Finance: A DeFi protocol that suffered a "bank run" in 2021, leading to the collapse of its TITAN token and significant investor losses.
- Acorn Collective: A blockchain crowdfunding platform that ceased operations in 2019 due to funding challenges and the collapse of the ICO market.
- CryptoZoo: Promoted by influencer Logan Paul, this NFT-based game failed to deliver a playable product, leading to investor backlash and legal issues.
Success Story:
- Ethereum: Launched in 2015, Ethereum introduced smart contracts, enabling a wide range of decentralized applications and becoming a foundational platform in the blockchain ecosystem.

AI's Current Trajectory

The AI sector, particularly generative AI, has seen explosive growth since 2023. However, as with previous tech booms, there's a risk of overvaluation and unmet expectations. Startups focusing solely on technological prowess without addressing real-world problems may find sustainability challenging.

The Gartner Perspective

Gartner's 2023 Hype Cycle for Emerging Technologies highlights the phases technologies undergo—from innovation triggers to peaks of inflated expectations, troughs of disillusionment, and eventual plateaus of productivity. AI technologies, including generative AI, are currently at varying points on this cycle, emphasizing the need for strategic planning and realistic goal-setting.

Conclusion

History has shown that technological revolutions often follow a pattern: initial excitement, rapid investment, overhype, and eventual market corrections. Success in these cycles doesn't solely depend on technological innovation but on understanding and addressing genuine consumer needs. As we navigate the AI era, it's crucial to learn from past lessons, ensuring that solutions are not just advanced but also relevant and sustainable.

Lessons from IoT and Blockchain​

IoT: The Promise and the Pitfalls​

Blockchain: Hype vs. Reality​

AI's Current Trajectory​

The Gartner Perspective​

Conclusion​

References