🕒 4 min read
By Myrin New, Senior IT Professional and Consultant
For much of my career, consulting followed a predictable formula — gather data, analyze patterns, draft recommendations, and present solutions. That framework worked when information was scarce and analysis required teams of specialists. But artificial intelligence has rewritten those rules.
Today, AI performs in seconds what once required weeks of coordinated effort from junior analysts and developers. As a senior IT professional, I’ve experienced this transformation firsthand. I no longer rely on large teams to collect or interpret data. Instead, I use AI to handle the technical and analytical groundwork, freeing me to focus on strategy, innovation, and business alignment.
The collapse of the traditional pyramid
Consulting has historically operated on a pyramid structure: a broad base of junior consultants supporting a narrow group of senior leaders. This model worked because analysis, modeling, and reporting were labor-intensive. But AI has automated those foundational tasks.
In my daily work, I use machine learning systems, predictive analytics, and generative AI to identify trends, debug systems, and produce complete reports before traditional teams have even finished their first meeting. The result is not simply faster delivery — it’s smarter consulting.
The pyramid is giving way to something more efficient: smaller teams built around expertise and automation rather than hierarchy and volume.
From pyramid to obelisk
The emerging model of consulting looks less like a pyramid and more like an obelisk — tall, lean, and precise. Instead of dozens of analysts supporting a few partners, the future revolves around three roles that I see playing out in my own projects:
- AI facilitators – professionals who design, configure, and refine AI-driven workflows.
- Engagement architects – experienced consultants who interpret AI outputs, validate insights, and translate them into actionable strategies.
- Client leaders – trusted advisors who maintain long-term relationships and guide organizations through digital transformation.
In my practice, this model means smaller, high-performing teams with higher leverage per person. AI handles data, while people handle direction. The result is sharper thinking, faster turnaround, and reduced overhead.
Why traditional firms resist
Many established consulting firms struggle to adopt this model because their economics depend on headcount. Their culture and compensation systems are built around billable hours and incremental promotion structures. Even as they introduce AI tools, those tools are often isolated in innovation labs or side projects — not integrated into the core of their operations.
By contrast, independent consultants and small firms have the agility to embed AI directly into workflows. We are not constrained by legacy systems or rigid hierarchies. We can adapt our processes the moment technology evolves.
AI in real-world consulting
In my projects, AI is not an abstract concept — it’s a daily instrument of efficiency. I use AI to perform SWOT analyses, identify database anomalies, streamline code reviews, and validate software integrations. What once required multiple analysts and endless meetings now happens in a fraction of the time.
For clients, this means reduced costs, faster implementation, and insights rooted in live data rather than static reports. The conversation has shifted from “how long will it take?” to “how soon can we act on it?”
Ethics and accountability in the AI era
Despite the promise of automation, human judgment remains essential. AI accelerates discovery but cannot replace ethical reasoning or accountability. Each recommendation I deliver is verified through cross-checking and review. In consulting, integrity still defines credibility, no matter how advanced the tools become.
The future of consulting will require governance models that ensure AI-assisted decisions are transparent, equitable, and responsible.
The new consulting advantage
AI isn’t replacing consultants; it’s replacing inefficiency. Firms and professionals that embrace this shift will deliver sharper insights, faster execution, and measurable outcomes. Those that cling to outdated models will struggle to justify their overhead.
As a senior IT professional, I’ve seen that success now depends less on scale and more on speed, strategy, and substance. The winners will not be those who talk about digital transformation — they will be the ones who have already built it into the core of their operations.
