Artificial intelligence (AI) has been celebrated as a game-changer for its transformative potential across multiple sectors, offering a value proposition of increased efficiency, innovation, and a reshaping of business operations. However, the hype surrounding AI also presents risk, specifically when the expectations it creates do not align with reality. Exaggerated claims and a disconnect between promise and performance can lead enterprises toward costly investments.
As enterprises integrate AI into their business models, they face a challenge of distinguishing between “genuine” innovation and “marketing” hype. This dilemma is known as “Shiny Object Syndrome (SOS)”, a cognitive bias where tech professionals and leaders are captivated by the allure of new, headline-grabbing technologies. SOS is characterized by the impulsive pursuit of new innovations without a thorough evaluation of their relevance or practicality for ongoing projects. This can distract focus from strategic objectives and business needs, leading teams to chase after the latest trends that may offer minimal value but come at a significant adoption cost.
So, does SOS make AI hype an actual risk for enterprises? Furthermore, how can organizations guard against the appeal of these “shiny objects” and ensure focus on implementing AI technologies that deliver tangible, value-driven results?
Understanding the AI Hype Cycle
The AI hype cycle is described by inflated expectations driven by media, aggressive marketing by AI vendors and a general misunderstanding of AI capabilities. This can lead to strategic mistakes and the misallocation of resources. In an interview, Linux pioneer, Linus Torvalds, expressed mixed feelings about AI. While recognizing AI’s potential to change the world, he is put off by the relentless hype surrounding it. “I think AI is really interesting... And, at the same time, I hate the hype cycle so much that I really don’t want to go there,” Torvalds explained, indicating his current strategy is to ignore AI until it stabilizes. He criticized the industry, noting, “It is currently 90% marketing and 10% reality.”
Linus Torvalds’ critique of the AI industry reveals a widespread issue in technology: shiny object syndrome and its triggers, such as:
- A strong pressure to innovate pushes development teams to explore emerging technologies without defined objectives. While this enthusiasm may lead to groundbreaking developments, a lack of discipline often results in unfocused efforts, limited progress, or a disconnect with business strategy.
- Innovative technologies are often oversold as silver-bullet solutions, leading organizations to adopt them without a thorough understanding of their practical uses or how they should be integrated into existing systems.
- The fear of missing out is common among leadership teams, causing them to adopt innovative technologies due to concerns about being outpaced by competitors. This mindset can lead to hurried decisions to keep up with industry peers, often without a thorough evaluation of whether the technology offers a competitive advantage.
These factors together challenge enterprises to balance innovation with strategic focus and long-term value creation.
AI Hype and Risk
While AI offers opportunities for innovation and efficiency, the excitement it creates can lead to unrealistic expectations. There are several sources of risk:
- No return on investment—Enterprises may invest substantial financial and human resources into AI projects without a clear return on investment.
- Neglected infrastructure—In the rush to deploy AI, critical steps such as establishing appropriate data infrastructure may be overlooked, resulting in unreliable system performance and poor adoption.
- Employee frustration—Employees may feel demotivated and disconnected if they perceive their efforts on AI projects to be unrelated to business needs or do not progress over time.
A balanced approach to AI integration that prioritizes strategic alignment and operational readiness is necessary to mitigate any potential risk.
Strategies to Effectively Manage AI Hype
AI is not a silver bullet; it is a feature in a software product. The true value of AI is its ability to improve processes—making them faster, more accurate, and capable of addressing genuine organizational challenges. There are six strategies organizations can utilize to manage AI hype and ensure appropriate technology adoption:
- Conduct a needs assessment—Enterprises need to identify the specific business challenge it plans to address. For example, a logistics company might explore AI for route optimization but find that a simpler software solution achieves their goals more efficiently and cost effectively.
- Invest in AI literacy—Enterprise-wide understanding of AI is important; workshops can educate everyone—from executives to staff—on its realistic capabilities and limitations.
- Adopt a phased approach—Gradual integration of AI can help organizations better manage risk. For instance, a multinational organization might start with AI-driven analytics in one department or region, assess its impact, and based on these insights, gradually expand the implementation across other areas.
- Strengthen governance and oversight—Establish governance frameworks for oversight of AI technologies. For example, a defined decision-making process can keep project direction clear and coherent, prevent unauthorized actions, and align with strategic goals.
- Engage with experts—Collaborating with AI experts and ethicists can help guide complex implementation challenges. For instance, financial institutions might benefit from consulting AI ethics experts to ensure that their AI-driven credit scoring systems are unbiased and comply with data privacy laws.
By focusing on these strategies, enterprises can navigate AI hype with a disciplined approach, selecting technologies that meet business needs and deliver value through open dialogue, collaboration and ongoing education.
Balancing AI Hype and Real-world Applications
As organizations continue to explore AI capabilities, it is important to remain aware of AI hype and the allure of SOS. The promise of AI as a cure-all for business challenges can lead to rushed decisions, misallocated resources, and disappointment when results fall short of expectations. To mitigate risk, organizations must adopt a methodical approach to AI implementation. This includes thorough assessments of technological suitability for specific business needs, investment in AI literacy to demystify the technology for all stakeholders, and strategic oversight to ensure that AI initiatives align with business objectives.
By doing so, enterprises can use AI’s potential to enhance operational efficiency and innovation, while avoiding the costly distractions of unproven technologies. Managing AI hype is not about curbing enthusiasm but strategically channeling it toward transformative, value-driven outcomes.
Mary Carmichael, CRISC, CISA, CPA CMA, COSO ERM
Is an enterprise risk management consultant, with a career spanning over 15 years. Specializing in technology risk management, she has consulted in various sectors such as education, utilities, government, and energy. In her roles with ISACA®, Mary serves on the Global CRISC Certification Committee and the Emerging Trends Working Group, and she is the vice president of the Vancouver, Canada Chapter. Her work focuses on the evolution of risk management, with a particular interest in the role of AI and its impact on Governance, Risk Management, and Compliance (GRC) in organizations.
Mary is a recognized speaker at global conferences such as VIPSS, InfoSec, and ISACA®, where she discusses AI and its effects on cybersecurity. She has also authored white papers including: “Using Risk Tolerance for Enterprise Strategy” and “Incorporating Risk Management in Agile Projects.”