Before the digital age hit full stride, adopting new technology was often a leap of faith—an expensive and risky one. Leaders operated in a limited market dominated by a handful of major players, like IBM, where systems were often rigid, proprietary, and incompatible with competitors. With high costs and few options, most businesses were faced with two choices: invest in complex systems or manage their business with manual processes.
- Challenges of early adoption: Implementing these systems was fraught with unknowns, resulting in businesses making tech investments cautiously and only when absolutely necessary. Customization and scalability remained elusive, making meaningful tech upgrades rare.
- Today’s fast-paced technology: In contrast, the pace of innovation today has changed significantly. What once felt like a cautious bet is now a desperate race. New trends emerge faster than ever, creating an urgency for companies to keep up or risk falling behind.
- Industry perspective: Tim O'Reilly, CEO of a renowned learning company, captured this sentiment in shift perfectly: "Every industry and every organization will have to transform itself... What is coming at it and bigger than the original internet, and you need to understand it, get on board with it, and figure out how to transform your business."
Nowhere is this pressure clearer than in the realm of AI and Copilot technologies, which hold the promise of transformative impacts across industries. But integrating AI effectively requires more than access to the latest tools; it demands a strategic, measured approach to where AI can truly add value. Leaders must avoid the pitfall of and resist AI FOMO (fear of missing out);, instead the focus should be on aligning AI capabilities with both current operations and long-term growth goals.
Understanding AI FOMO: the psychology behind the urge to adopt
Diving into the psychology behind technology-driven FOMO is complex and layered by a series of key motivators. Streamlined workforce, futureproofing, realized profit gains. These are all valid reasons, and it is not a hyperbole to say that leaders today are feeling mounting pressures to adopt cutting-edge tools because rival competitors may be well on their way to massive breakthroughs with AI-driven innovations. For example, over 55% of companies globally have already incorporated AI in some way, largely due to expectations that it can significantly enhance competitive advantage. This fear is further compounded by vendors and media hype that paint AI as quintessential driver of success. Furthermore, the FOMO in tech adoption can cloud decision-making for those in leadership positions as they strive to prioritize short-term gains or status over long-term strategic alignment for their companies.
Leaders should instead ask: What specific business outcomes do we aim to achieve with AI? Currently, only about 4% of businesses are leveraging AI to drive meaningful innovation across their operations. This dissonance that many companies are ailing from to properly implement AI strategically suggests that pressures to adopt AI—often fueled by competitive FOMO—can lead to rushed and superficial implementations. Aligning AI initiatives with clear goals can mitigate this FOMO-driven rush and help prevent implementing AI solutions that ultimately don’t address pressing organizational needs.
What do you need to know now, and what will you need in the future?
Distinguishing between AI tools that solve immediate organizational pain points and those that will contribute to future growth of its business is crucial. This distinction will determine the proper path towards sustainable and impactful AI adoption and requires both a clear understanding of the business’s current state and a vision for where it should be in the future.
Take Microsoft’s AI Copilot, which offers real-time assistance across a variety of productivity tools and applies blanket uses for many department operations. For some businesses, Copilot’s benefits are immediate—they can streamline data management, reduce manual processes, and increase productivity immediately. Timing is crucial: adopting advanced technologies prematurely often results in a lack of integration, inconsistent workflows, and resistance from employees who aren’t ready for a dramatic change.
4 organizational blockers to a successful AI transition
Even under ideal circumstances and preparation, organizations can still face numerous organizational blockers that can ultimately hinder AI implementation success. Here’s a detailed rundown of critical pitfalls to be aware of and avoid:
1. Concurrent technology migrations
Organizations often face the challenge of integrating AI while simultaneously modernizing legacy systems. When older systems are still being replaced or upgraded, introducing a sophisticated AI can overburden IT resources and lead to fragmented data management. A case in point is when the UK’s NHS (National Health Services) implemented AI-driven scheduling systems for surgeries while also undergoing electronic health record migrations. The dual projects caused delays and integration issues, highlighting the risks of simultaneous tech transitions.
2. Skill and culture gaps
AI adoption requires specific skill sets, and without proper training, employees may resist or underutilize the technology. For example, Walmart’s AI-powered scheduling system faced backlash from employees unprepared to adapt to the automated system’s changes in shift allocation. Such resistance can undermine the value of AI, stressing the need for adequate employee training and engagement as part of AI rollouts.
3. Incomplete or poor data infrastructure
AI relies on vast amounts of precise, high-quality data,; but many organizations have yet to establish data governance frameworks and clean data pipelines. The success of AI implementations at companies such as Netflix, which uses AI to personalize user recommendations, demonstrates the importance of structured data of relevance. In contrast, organizations that lack robust data practices often find their AI systems inaccurate or unresponsive, diminishing their value.
4. Strategic misalignment
You have probably heard this a lot already: AI projects should not function as stand-alone endeavors but rather as part of a larger business plan. IBM’s Watson experienced setbacks in healthcare because of unrealistic expectations and limited integration with actual clinical workflows. Without clearly aligned goals, even high-potential AI technologies can struggle to deliver value.
Learning from success and complications in AI implementation
AI Success story: UPS’s Orion Algorithm
UPS exemplified strategic AI adoption with its Orion route optimization algorithm. By implementing AI to solve a specific, well-understood issue (route efficiency), UPS saved millions in fuel costs and improved delivery times. This success was possible because UPS matched its AI initiative with a clearly defined need, data readiness, and a phased deployment strategy that allowed for ongoing adjustments.
Complications in AI integration
One major tax services company’s adoption of a prominent AI system for customer support offers a cautionary tale. The integration faced challenges, partly due to limitations in the AI's ability to adapt to complex tax scenarios and difficulties in merging automated insights with real-time customer interactions. The impact was restricted because the company’s goals were not fully aligned with the AI system’s practical capabilities, underscoring the importance of setting realistic, achievable objectives in AI initiatives.
Invest in a disciplined future-proof AI strategy
The FOMO effect around AI and Copilot technologies can be an intoxicating and potent driver, but unexamined urgency often leads to lapses in judgement. By focusing on clear objectives, assessing organizational readiness, and considering both current needs and future goals, leaders can harness AI’s transformative potential responsibly.
Here at Alithya we understand that success lies not in following trends but in making informed, intentional decisions that align with an organization’s unique path to sustained growth. With over 30 years of experience guiding businesses through digital transformation, we’re well-equipped to help you navigate this critical juncture. Contact us today to explore how a strategic, disciplined approach can maximize your AI and Copilot technology investments, setting you on the right path for long-term and sustainable growth.