AI Hype Overshadowing Simpler, More Effective Solutions

The quest for AI-driven solutions may be overshadowing simpler, more effective approaches in many cases, as organizations focus on how AI can improve processes rather than first identifying if improvement is truly needed.

Solution driving requirements, not vice versa: A recent working group on using AI and machine learning to improve network utilization exemplified this trend, with the goal of applying AI taking precedence over assessing the actual need for improvement:

• One participant shared an anecdote about a customer requesting an “AI-based” solution for WAN failover, rejecting a simple, time-tested option in favor of an unnecessarily complex AI approach.
• This mindset mirrors the working group’s focus on how AI could enhance network utilization, rather than first determining if current utilization genuinely required improvement.

The allure and pitfalls of AI: As discussions about making AI more “explainable” and “transparent” continue, it’s crucial to recognize that in many scenarios, the perceived need for AI may be driving requirements, leading to overcomplicated solutions:

• In cases like the WAN failover example, a basic algorithm or existing technology might suffice, proving more efficient and cost-effective than an AI-driven approach.
• Organizations should carefully evaluate whether AI is truly necessary for a given problem, or if simpler, more straightforward solutions could achieve the desired outcomes without the added complexity and potential drawbacks of AI.

Analyzing deeper: The inclination to view AI as a panacea for all problems may stem from its current hype and the fear of falling behind in adopting cutting-edge technology. However, this mindset risks overlooking the value of proven, non-AI solutions and could lead to wasted resources and suboptimal results. By focusing first on clearly defining the problem and desired outcomes, organizations can make more informed decisions about whether AI is the most appropriate tool for the job, or if a more straightforward algorithmic approach would suffice.