When AI Helps Build the Software, Who Helps Build the Strategy?

A decade ago, many enterprise software projects began with a familiar ritual that started with a requirements document, a kickoff deck, a few workshops, and someone bravely saying, “Yes, we can build that.”

That pattern is already starting to shift across organizations. With AI-assisted coding tools, low-code platforms, design accelerators, and generative AI copilots, building software is becoming faster and more accessible. Gartner predicts that by 2028, 75% of enterprise software engineers will use AI code assistants, up from less than 10% in early 2023. McKinsey estimates generative AI could add $2.6 trillion to $4.4 trillion annually in economic value across analyzed use cases.

That signals a big shift. But faster building does not translate into better decision making or faster decisions. For instance, if customer reviews and feedback processes do not keep pace, the efficiency gained in development does not result in faster delivery. In fact, when AI makes it possible for teams to build almost anything, the harder question becomes what should we build, why, for whom, and what should we stop doing? That is where Product Consulting becomes more important than ever.

Moving From Execution to Strategy

Traditional software services often began after the client had already decided what they wanted. The role of the partner was to gather technical requirements, estimate effort, build the solution, and manage delivery.

That model will not disappear. Enterprises will still need great execution. But the center of gravity is shifting.

As AI accelerates delivery, clients will increasingly need partners who can help them interpret the market, understand changing customer expectations, and shape strategy before the backlog exists. This is especially true for non-tech enterprises in consumer-facing industries including restaurants, convenience stores, retail, hospitality, and consumer packaged goods. These businesses may not describe themselves as technology companies, but their customers experience them through technology every day.

A restaurant brand is not judged only by food quality or store experience anymore. Customers also evaluate mobile ordering, loyalty personalization, delivery visibility, payment convenience, and menu discovery. They also notice how well the brand remembers customer preferences without becoming “that app that knows too much.” The bar keeps moving because customers do not compare digital experiences within one industry. They compare everything to the best experience they had anywhere. If Spotify can personalize music, if Amazon can simplify buying, if Uber can show real-time arrival, then customers naturally wonder why ordering lunch sometimes still feels like filling out a small tax form.

The Rise of Product Consulting

Product Consulting is becoming more strategic because product decisions now carry more weight earlier in the process.

The broader management consulting market is projected to grow from $491.68 billion in 2025 to $721.60 billion by 2032, a 5.63% CAGR, according to Fortune Business Insights. Digital transformation consulting is growing even faster, with one estimate projecting the market to reach $896.21 billion by 2033, at an 11.2% CAGR.

The demand is shifting from technology implementation alone to the strategic guidance required to make better product and investment decisions. Enterprises need help answering questions like what customers will expect two years from now, which AI experiences are genuinely useful versus novelty with better lighting, how roadmaps should evolve as product cycles shrink, where AI can improve the customer journey without adding friction, and how to prioritize when every idea suddenly feels buildable.

At Bounteous, that is often the work we are helping clients do. We help decide where AI belongs in the product experience by bringing customer behavior, operational reality, available data, technical feasibility, and the business case into the product conversation. Product Consulting helps surface those questions before excitement turns into work no team can realistically deliver.

That matters because a promising AI idea still has to work for the people using it, the teams supporting it, and the systems behind it before it deserves a place on the roadmap.

For consumer businesses like restaurants, convenience stores, retail, and hospitality, this matters deeply. These industries are powered by physical operations, human behavior, brand trust, and everyday habits. Technology enables the business, but product strategy connects the technology to real customer value. For instance, a restaurant brand might say, “We want to use AI to improve guest experience and increase digital sales.” Product Consulting would translate that ambition into a tangible solution path, perhaps starting with an AI-powered reorder experience in the mobile app that uses loyalty history, menu availability, store hours, and previous basket data to recommend a one-tap repeat order. The Product team would define the customer journey, success metrics, personalization rules, fallback states, data needs, API dependencies, POS/menu constraints, privacy considerations, and phased rollout plan.

From there, the ambition becomes a real product slice, such as, “For known loyalty users, show a personalized reorder module on the app home screen, powered by past orders and current menu availability, with conversion, AOV, and repeat-purchase lift measured against a control group.” That is Product Consulting at work. It turns a broad AI ambition into something customers can use, engineers can build, operators can support, and the business can measure. It helps define the target experience, validate the customer need, assess technical feasibility, sequence the roadmap, and decide how success will be measured. It is the bridge between business strategy and technical execution.

AI Creates More Need for Product Judgment

One charming thing about AI is that it is very eager to help. Sometimes a little too eager. Ask it for five concepts, and it gives you fifteen. Ask it for a prototype, and suddenly the team has three possible futures, two dashboards, and a dining chatbot named D2B2.

This abundance is powerful. But abundance needs judgment.

Product consultants will increasingly become translators between technical possibility and business reality. They will help enterprises understand what AI can do, what customers need, what operations can support, what creates differentiation, and what should wait.

The future of product consulting is helping organizations become better at making choices. In an AI-enabled world, the advantage will belong to organizations that build faster, understand their customers sooner, learn continuously, and make better product decisions more consistently.

And thankfully, customers remain wonderfully human, impatient, emotional, loyal, distracted, delighted by small conveniences, and occasionally willing to forgive a bad app experience if the fries are good.

But probably not forever.