The late-afternoon sun poured gold over the playground as James spotted Oliver and Popeye on the swings, slicing clean arcs through the cool air. The woodchips shimmered beneath them, their long shadows stretching ahead like a sketch of the future they were about to unpack together. It felt almost too fitting: two consultants suspended mid-flight, debating a technology that might launch their careers higher than they ever dreamed, and knock a few people off their feet along the way.
James, a calm and seasoned senior consultant, strolled toward them with the relaxed confidence of someone who had weathered many so‑called “disruptions” and learned that most revolutions arrive disguised as new templates and stranger spreadsheets. Yet even he sensed that this moment was different. The change humming in the background felt bigger, faster, deeper, and undeniably more exhilarating.
“Look at you two,” he called, as Oliver and Popeye swung in near-perfect sync. “Two rising stars on a playground, already practicing for the velocity AI is about to add to your lives.”
Oliver laughed, leaning back to squeeze out a little more height. “It’s either training,” he said, “or a metaphor we’re not ready for.”
Popeye tightened her grip on the chains and smiled. “Definitely a metaphor,” she replied. “Because I don’t think either of us has really processed how high this thing might push us.”
James took the empty swing beside them but kept his feet on the ground. “That’s exactly the conversation I want,” he said. “No theory, no glossy decks. Let’s use this moment, the swings, the sun, the uncertainty, to talk about how AI will change your actual day‑to‑day work.”
The first push: from grunt work to acceleration
They started with the obvious. Oliver described how, in just a year, AI had started to quietly swallow the tasks that once defined the junior consulting experience: taking meticulous notes in long workshops, reading hundreds of pages of client documents, stitching together background research from scattered sources, drafting the first cut of slides. What used to demand late nights now happened in minutes with a well-crafted prompt. Instead of spending days organizing input, he could jump straight into testing hypotheses, exploring patterns, and shaping stories.
Popeye added that AI was becoming a kind of ever-present analyst, one that never got tired of summarizing, reorganizing, or rephrasing. She used it to digest messy transcripts, to transform rough bullet points into executive-ready language, and to generate alternate framings of the same problem for different audiences. The quantity of raw work didn’t shrink much, but the time between data and insight did. The grunt work had not vanished entirely; it had simply become the machine’s responsibility, freeing humans to focus on higher-order thinking.
James listened carefully. He had grown up in a world where professional credibility was often measured in hours spent inside spreadsheets. Hearing them talk about skipping entire layers of manual effort made him feel both slightly disoriented and deeply encouraged. The pyramid shape of consulting, the broad base of junior labor supporting a narrow decision-making top, was already warping into something flatter, faster, and more focused on judgment than repetition.
Rewriting the middle: analysis, design, and judgment
Once the three of them settled into a steady rhythm, two swings in the air, one anchored to the ground, they shifted to the more subtle layers of their work: analysis and solution design.
Oliver argued that AI had already narrowed the “capability gap” for less experienced consultants. Tasks that once required years of Excel practice or deep familiarity with an industry could now be approached with the help of smart tools that suggested formulas, created dashboards, or proposed first-pass segmentations. The tools didn’t eliminate the need to understand the business, but they made it much easier for someone early in their career to get a decent starting point quickly.
Popeye agreed, but pointed out the crucial catch: “AI is great at rolling everything up,” she said, “but it’s still terrible at knowing when something doesn’t smell right.” It wouldn’t necessarily flag a number that looked too good to be true or notice that two supposedly separate categories were, in practice, the same thing under different labels. For that, the team still needed human skepticism, pattern recognition, and a feel for how operations really worked. The more they leaned on AI for speed, the more they had to lean on their own judgment for validation.
Together, they described a new rhythm of work. AI ingests and structures the data; consultants interrogate it. AI proposes correlations; consultants decide which ones matter. AI drafts multiple solution paths; consultants weigh tradeoffs, politics, risk, and ethics. The tools made the “what” and “how” of potential solutions easier to see, but the “should we” and “when” of real decisions remained stubbornly human.
James liked that framing. It matched his lived experience: clients rarely paid for the ability to generate options; they paid for the courage to recommend one.
At the front of the room: AI and the human presence
Eventually, the conversation turned to the client-facing side of the job, the part that still made even seasoned consultants feel a flutter of nerves.
Could AI one day build and deliver an entire client presentation by itself? Oliver believed that, technically, yes. He could imagine a model pulling from project data, past deliverables, and external benchmarks to assemble a slick 25‑minute “movie”, a synthetic avatar walking the client through findings, scenarios, and recommendations. For more standardized offerings or price-sensitive clients, such a product might become normal. It was easy to picture firms selling lower-fee, AI-led briefings alongside more premium, human-led engagements.
Popeye, though, emphasized everything that would remain stubbornly analog. In-person workshops, tense steering committees, and sensitive leadership sessions hinge on micro-signals: a chair shifting uncomfortably, a CFO going quiet, a site manager rolling their eyes at a glossy efficiency claim. Reading and responding to those cues requires something AI doesn’t have, a body in the room, a sense of vulnerability, and the ability to feel the weight of silence. Even the most realistic avatar would struggle to replace that kind of presence.
James found himself nodding. AI could speak persuasively about the future, but it could not be accountable for it. The moment when a consultant looks a client in the eye and says “This is the path I recommend” still belongs to humans.
The heart of the role: imperfection, magic, and the living spark
As the swings slowed, James finally voiced the question that had been simmering beneath the whole discussion: in a world where AI can increasingly match or exceed human performance on many cognitive tasks, what makes the consultant’s role uniquely human?
He began with a belief that had crystallized over months of experimentation and doubt. AI, he said, would eventually become frighteningly close to perfect at many things, spotting patterns, generating language, predicting outcomes. But that very perfection made it incomplete. Human beings, by contrast, are gloriously inconsistent: prone to errors, shaped by emotion, constrained by limited information, and yet capable of acts of courage and creativity that no algorithm can predict. “Our imperfections,” he suggested, “are not flaws to be ironed out; they are part of what makes our judgment trustworthy.”
Oliver picked up the thread and framed it more forcefully. The current obsession with whether AI will “surpass” human intelligence, he argued, rests on a reductionist view of intelligence as pure calculation. In reality, there is something deeper at work in human consciousness, a mystery that science has not fully explained. “There is a kind of magic,” he said, “that animates molecules into life. That living spark, the awareness that can care, doubt, and sacrifice, is the highest form of intelligence.” In consulting terms, that spark is what allows a person to stand in a boardroom and argue for a path that benefits workers as well as shareholders, or to tell a powerful client that the numbers do not justify their preferred narrative.
Popeye added that this “living spark” also carries responsibility. Because humans, not AI, experience guilt, pride, and empathy, it must be humans who set the boundaries for how these tools are used. Consultants will need to become stewards of AI, not just power users: questioning data sources, exposing hidden biases, and pushing back when a technically optimal recommendation conflicts with ethical or social realities.
The three of them fell briefly silent. In the fading light, surrounded by the ordinary sounds of a playground, the question of AI suddenly felt less like a technical problem and more like a test of character.
A future we can’t quite picture
As the sun slid toward the horizon and the air grew cooler, they walked a slow loop around the playground, tracing irregular paths through the woodchips. Their footprints overlapped and diverged, much like the evolving relationship between human expertise and machine intelligence.
They imagined delivery models where AI ran continuous “background thinking” on a client’s data, surfacing issues long before anyone asked; consultants would step in to interpret, prioritize, and help leaders act. They talked about middle-market companies in distant regions gaining access to strategy support that previously only global giants could afford, because AI compressed the cost and time required to deliver high-quality analysis. They pictured juniors who spent their formative years not grinding through endless manual tasks but orchestrating AI workflows, leading structured problem-solving sessions, and learning to challenge the tools they used.
James recognized that none of this was guaranteed. Firms could cling to old models, treat AI as a mere cost-cutting lever, and hollow out their own talent base. Or they could treat this moment as an invitation to redesign their business around faster learning cycles, broader access, and a more explicit commitment to human judgment and responsibility.
When they finally returned to the swings, the lights had come on, casting soft halos over the empty seats. Oliver and Popeye stood on either side of James, each holding a chain, each looking out into a darkness that was just beginning to thicken.
“Whatever happens next,” Oliver said, “it won’t look exactly like any of the neat scenarios in our decks.”
Popeye smiled. “That’s what makes it exciting.”
James looked at them, two consultants at very different stages of their careers, both staring into an unknowable future, and felt a strange combination of calm and anticipation. The only certainty, he realized, was that their predictions would be wrong in interesting ways.
He tightened his grip on the swing and offered the only closing he felt truly fit the moment:
“If tomorrow resembles today in any way, we should expect it to be very different from what we imagine now, after all, I could not have predicted yesterday what I am witnessing today..”
MB with S. Robinson and D. Zurel
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