March 13, 2025
Today’s buzz around agentic AI perfectly illustrates the balance we need. Forbes boldly predicts that “2025 will be the year of AI agents,” and indeed, breakthroughs in agentic systems are transforming how tasks from customer support to complex research can be automated. For example, Deep Research is an AI agent that can dramatically reduce the time needed for research and analysis.
Yet, the excitement and fear of missing out have led some to deploy agentic AI even when simpler workflows would suffice. Consider CrewAI, one of the best tools for Agentic AI, which claims that 40% of Fortune 500 companies are using its framework. The real question is: how many of these implementations solve complex challenges autonomously in production? A straightforward, well-designed workflow can often achieve the desired outcome without additional complexity.
At Equal Experts, my experience has taught us that smart innovation isn’t about using the flashiest technology – it’s about aligning solutions with real business needs. I was particularly struck by Anthropic’s blog post on effective agents, which echoes a principle I’ve seen in practice:
“When building applications with LLMs, we recommend finding the simplest solution possible and only increasing complexity when needed. This might mean not building agentic systems at all. Agentic systems often trade latency and cost for better task performance, and you should consider when this tradeoff makes sense.”
This means starting with focused, well-defined solutions and only scaling up when the value is proven. In many scenarios, a straightforward workflow enhanced by targeted AI capabilities delivers transformative results more reliably and efficiently than an over-engineered agentic system.
While enthusiasm for new AI trends is understandable, deep, technical knowledge is essential to navigate the complexities of AI. Understanding the underlying techniques and model limitations empowers us to make informed decisions about costly missteps and overcomplicated solutions. It’s not enough to rely on buzzwords or surface-level understanding; the real power of AI lies in the details. Deep knowledge lets us discern when advanced techniques are essential versus a more straightforward method. This foundation is what transforms AI hype into strategic, measurable success.
In my work, I’ve observed three common attitudes toward AI implementation:
I must confess that my inner tech enthusiast is always excited by new AI capabilities. However, experience has taught me to temper that enthusiasm with pragmatism. Before diving into a new AI trend, I ask:
I’m not pessimistic at all – in fact, I’m genuinely excited about what this year holds for AI. The future of enterprise AI is auspicious, and we’re in an era of breakthroughs. However, with the constant media hype and market pressure, focusing on what truly drives value is more important than ever. I’ve seen firsthand how over-engineering can derail promising projects. The path to successful AI transformation lies in balancing visionary ideas with pragmatic implementation.
We must always strive to cut through the noise, ensuring our solutions remain innovative and practical. This approach is not about stifling creativity but fostering innovation that delivers measurable, lasting impact. And if you’re hearing me, you’re in the right place to get a clear, grounded perspective on AI’s evolving landscape.
By focusing on strategic implementation and remaining vigilant against unnecessary complexity, organisations can harness AI’s revolutionary potential without losing sight of what genuinely matters-effective, efficient, and sustainable business solutions.
All business models have their pros and cons. But, when you consider the type of problems we help our clients to solve at Equal Experts, it’s worth thinking about the level of experience and the best consultancy approach to solve them.
If you’d like to find out more about working with us – get in touch. We’d love to hear from you.
