What Does a Generative AI Consultant Actually Do? (And Why Your Business Needs One)

Let’s be frank. The term “Generative AI” is now so ubiquitous it risks becoming meaningless. It is the headline act at every business conference and the proclaimed solution to every corporate ailment. This is not mere speculation; workplace adoption of AI has skyrocketed from 22% to an astonishing 75% in a remarkably short period. ¹

Behind this rapid ascent, however, lies a chasm between the technology’s much-hyped potential and its practical, profitable implementation. Business leaders everywhere are asking the right question: “How do we progress from generic tools like ChatGPT to using AI to solve our specific, complex business problems?”

The answer lies not in acquiring more software, but in securing the right strategic partner.

This is the domain of the Generative AI consultant. Think of them not as a technologist, but as a master locksmith. Their role is not simply to understand the lock; it is to understand the door, the room, and the treasure you are trying to reach. They are the essential bridge between the abstract power of AI and the concrete business outcomes every organisation seeks: reduced costs, minimised errors, and increased efficiencies that directly enhance financial performance. ²

This guide will pull back the curtain on what a consultant does. We will move beyond the buzzwords to explore their three core functions: architecting a coherent strategy, executing a bespoke AI-driven transformation, and, most critically, proving its measurable value.

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It All Starts with “Why”: The Strategy-First Approach

The most critical function of a top-tier AI consultant occurs long before a single line of code is written: a deep, strategic diagnosis of the business itself. Many AI initiatives are destined to fail because they start with a technology (“we need a chatbot”) instead of a well-defined problem. A skilled consultant inverts this flawed approach, beginning not by asking “what,” but by asking “why.”

This initial phase is not about selling a solution; it is about building a shared understanding. For many organisations, daily operations can create a form of tunnel vision, making it difficult to step back and perceive the broader strategic landscape. ³ The consultant acts as an objective catalyst, facilitating a process of discovery that brings clarity and forces internal alignment on priorities—a valuable asset that prevents the misallocation of resources on poorly conceived projects. They do not just receive a brief; they co-create it.

The Diagnostic Process in Detail

This structured investigation into the core of your business typically involves three key stages:

• Defining Your Goals: The process starts with a lucid understanding of your primary business objectives. ^4,5 Through workshops and interviews, the consultant answers fundamental questions: Is the principal aim to reduce operational costs? To improve customer satisfaction scores? To accelerate time-to-market? ^6,7 Without this clarity, any technology implementation is rudderless.
• Identifying the Real Pain Points: With goals established, the consultant maps existing workflows to identify operational bottlenecks. ³ They act as an impartial observer, pinpointing where manual, repetitive, and error-prone tasks consume valuable employee time and create organisational friction. ⁸
• Auditing Your Systems and Data: A thorough assessment of your current technology stack is essential. The consultant evaluates existing software, infrastructure, and data sources to understand capabilities and vulnerabilities, ensuring any new AI solution can be securely integrated with the systems upon which you already rely. ^2,9,10

Your Actionable Blueprint

This intensive diagnostic phase culminates not in a sales pitch, but in a tangible, actionable plan. At OpenKit, this is our AI Strategy Consultancy offering, designed to give leadership teams the clarity to make informed investment decisions. ² The deliverable is a business document, not a technical one, that typically includes:

• An AI Strategy Report: Outlining the highest-impact opportunities for AI, explicitly linking each one to your strategic goals.
• A “Build vs. Buy” Analysis: Rigorous, impartial advice on whether an off-the-shelf tool can meet your needs or if a bespoke solution is required to solve a unique challenge. ²
• An Implementation Roadmap: A clear, phased plan for execution with projected timelines, resource requirements, and cost estimates, transforming a vague intention into a concrete project plan. ^2,11

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How AI Actually Transforms Your Business: The Three Pillars of Value

Once a clear strategy is in place, the consultant’s role shifts to execution. This work is best understood as three interconnected pillars of value creation that fundamentally transform how a business operates. At OpenKit, we structure our work around this proven framework: Automating and Optimising, Activating Knowledge, and Empowering Teams. ²

Pillar 1: Automating the Grind to Unleash Your Team

The most immediate application of generative AI is intelligent automation. The goal is to replace manual, repetitive tasks with sophisticated AI agents, freeing your team to focus on high-impact work that demands creativity and critical thinking. ^2,8,12

For many businesses, this is the key to scalable growth. Traditionally, as a business expands, its operational costs increase linearly. More customers mean more support tickets, which means hiring more agents. AI automation breaks this restrictive relationship, ¹ allowing you to handle a significant increase in workload without a proportional rise in expenditure. Instead of hiring thirty customer service agents, you might hire three highly-skilled agents augmented by a powerful AI system. ¹³ This is not merely about saving money; it is about architecting a more scalable and profitable business model.

Practical applications span every department:

• Customer Service Transformation: Implement AI-powered chatbots that provide 24/7 support, instantly handling common questions and intelligently escalating complex issues to a human agent. ^13,14,15 This reduces waiting times, improves customer satisfaction, and lowers operational costs. ^16,17 Advanced systems can even use sentiment analysis to address customer frustration proactively. ¹⁸
• Marketing and Sales Acceleration: Build systems that automate the creation of first drafts for blog posts, social media updates, and email campaigns. ^14,19,20 These systems can generate highly personalised marketing copy at scale, tailoring messages to different audiences to increase conversion rates. ²¹ For sales teams, AI assistants can draft outreach emails or generate talking points for calls. ¹⁴
• Streamlining Core Operations: Automate processes like intelligent document processing (IDP) to extract key information from invoices and contracts, eliminating hours of manual data entry and minimising the risk of costly human errors. ^1,22

Pillar 2: Unlocking Your Company’s Hidden Brain

Every organisation possesses a vast, untapped asset: the collective knowledge locked away in “unstructured data”—the countless PDFs, emails, chat logs, and meeting transcripts that accumulate daily. ^10,23,24 This information is often fragmented, siloed, and effectively unsearchable. ²⁵

A consultant’s role here is to transform this chaos into a secure, centralised, and interactive corporate knowledge base. This is a core competency for OpenKit, demonstrated in our work building platforms like the BAISICS enterprise tool that revolutionises legal document review. ²

Creating a bespoke, internal knowledge engine builds a unique competitive advantage. Public AI models like ChatGPT are trained on the public internet; they have no knowledge of your confidential projects or internal processes. ^22,26 Your “private brain” becomes a strategic moat. This also addresses a critical vulnerability: the loss of institutional knowledge when experienced employees leave. ²⁷ By capturing expert knowledge within the system, you transform fragile individual expertise into a durable organisational asset. ²

The technical process, in simple terms, involves:

1. Data Ingestion: Securely connecting to your data repositories (e.g., SharePoint, Google Drive) to pull in documents automatically. ¹⁰
2. Processing and Embedding: The AI “reads” and comprehends the content, converting its understanding of the text’s meaning and context into a sophisticated mathematical representation called an “embedding.” ^10,23
3. Indexing and Retrieval: These embeddings are stored in a specialised “vector database” that enables “semantic search,” finding information based on meaning, not just keywords. ^23,28
4. Conversational Interface: A user-friendly front-end (like a secure chatbot) allows employees to ask complex questions in plain English and receive concise, accurate answers synthesised from company documents, complete with citations. ^10,28,29 This is often achieved using Retrieval-Augmented Generation (RAG), which grounds the AI’s response in your own trusted data, preventing the “hallucinations” of public models. ²³

Pillar 3: Empowering Teams with Intelligent Co-Pilots

The narrative around AI is often dominated by a misleading focus on job replacement. A strategic consultant knows the true power of AI lies in augmentation. The goal is to build tools that act as intelligent “co-pilots,” enhancing the capabilities of human experts so they can perform their jobs faster and more accurately. ^2,14,27

AI is most effective when it takes over specific, high-friction tasks within a complex job, rather than replacing the entire role. ²⁷ By removing the drudgery, these empowerment tools not only boost productivity but also demonstrably increase employee satisfaction and retention. ⁶ When skilled professionals are less burdened by repetitive work, they have more time for strategic thinking and innovation. ^1,6,8 This creates a powerful virtuous cycle: improved efficiency leads to higher job satisfaction, which in turn fosters a more innovative and competitive company culture.

The practical applications of this philosophy are particularly transformative in document-intensive industries such as law, insurance, and finance.

• For Legal Professionals: The core of legal work involves meticulous document review—a process that is both time-consuming and mentally taxing. A consultant’s first step is to map these day-to-day processes to find the single workflow that, if automated, would free the largest block of a fee-earner’s time. For commercial property law firm Morgan & Clarke, that task was due diligence on large, often poorly-scanned commercial leases. OpenKit developed a bespoke AI tool that turned a 120-minute manual indexing task into a 10-minute, AI-assisted click-through process. This is the power of a targeted solution, enabled by platforms like BAISICS, an enterprise AI system built by OpenKit. As Christopher Wright, Director at BAISICS, notes, “Working with OpenKit has been transformative for our business. Their solution delivers exceptional performance for our specific needs while remaining remarkably easy to verify and trust.”
• For Insurance Underwriting and Claims: The insurance industry is built on assessing risk and processing claims, both document-heavy workflows. An AI co-pilot can streamline underwriting by ingesting and analysing thousands of policy documents, historical claims data, and third-party risk reports to provide underwriters with a comprehensive risk summary in seconds. In claims processing, the AI can automate the initial review of claim forms and repair estimates, flagging anomalies for human review and fast-tracking standard claims. This not only accelerates settlement times but also empowers claims adjusters to focus their expertise on the most complex cases.
• For Private Equity Due Diligence: A private equity deal hinges on a rapid and thorough due diligence process, often involving a virtual data room containing thousands of documents. An AI-powered co-pilot can systematically analyse this entire data room, extracting critical financial data, identifying non-standard clauses in contracts, and summarising key findings from market research reports. Instead of an analyst spending weeks manually reading documents, they can query the AI system (e.g., “Summarise all change-of-control clauses across the target’s customer contracts”) and receive a synthesised, actionable report in minutes, allowing the deal team to make faster, more informed investment decisions.

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The Pragmatist’s Approach: A Relentless Focus on Measurable ROI

A credible Generative AI consultant is a commercial partner whose success is tied to yours. Every recommendation and every line of code must be justifiable in terms of measurable business value and a clear return on investment (ROI). ^2,7

Demystifying and calculating the ROI of an AI project is a core function. The standard formula is straightforward:

The consultant’s expertise lies in accurately defining the terms. “Total Investment” includes all associated expenses: development time, infrastructure costs, and employee training. ^11,32 “Net Benefit” requires capturing the full spectrum of value created.

The following table provides a practical framework for measuring the impact of an AI investment, translating abstract benefits into concrete metrics to build a compelling business case.

De-Risking Your Investment with a “Rapid Impact Pilot”

To move from estimates to hard data, the most pragmatic approach is a focused pilot project. This methodology, the basis of OpenKit’s Rapid Impact Pilot model, de-risks your investment. ² Instead of committing to a large project based on projections, we target your most critical business challenge and build a focused, operational solution designed to deliver measurable results in under three months. This provides a clear, data-driven case for a full-scale build, with an ROI calculation based on real-world performance, not assumptions. ^2,11

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Finding the Right Partner: A 5-Point Checklist

The success of any AI initiative depends on the partner you choose. This evaluation helps distinguish between a “vendor” who sells a product and a “partner” who collaborates to solve a complex problem. For bespoke AI, the partnership model is the only one that reliably leads to success. ²

Here is a checklist for identifying a genuine AI consulting partner:

1. A Portfolio of Real-World Success: Do not be swayed by slick presentations. The most important credential is a proven track record. Ask to see a portfolio of completed projects and detailed case studies, ideally in your industry. ^3,5 A strong portfolio, such as OpenKit’s work with the Department for Education and legal firms, demonstrates versatility and the ability to deliver. ²
2. Direct Access to Technical Experts: A common frustration is being firewalled from the technical team by account managers. Insist on a clear point of contact and direct access to the senior experts building your solution. ^2,5 This is a core principle at OpenKit, ensuring clarity and rapid problem-solving. ²
3. A Commitment to Bespoke Solutions: Be wary of any potential partner who immediately pushes a specific product before they have thoroughly diagnosed your needs. A true partner’s value lies in their ability to design a solution tailored to your unique requirements, especially where generic tools fall short. ^2,9 Their process should always begin with a deep dive, not a product demo.
4. Full Lifecycle Support: The project does not end at launch. Ask: “What happens next?” A genuine partner offers comprehensive support “before, during, and after launch,” including ongoing maintenance, security updates, and a plan for future upgrades. ^2,9 This ensures your investment continues to deliver value.
5. A Focus on Your Business Goals: Does the consultant speak your language? They should be as fluent discussing business KPIs, cost savings, and revenue impact as they are discussing algorithms. ⁷ Their proposals and progress reports should be framed around business outcomes, not just technical tasks. ⁴

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Conclusion: Your Partner in Business Transformation

A Generative AI consultant is far more than a programmer or a technologist. They are a multifaceted professional who acts as a strategist, aligning AI with your most important business goals; an architect, designing robust, bespoke solutions; and a pragmatist, ensuring every action taken and every pound spent is tied to delivering measurable, tangible value.

The ultimate objective is not simply to “do AI.” It is to use AI as a powerful lever to build a more efficient operation, activate your organisation’s hidden knowledge, and empower your team to innovate and win in an increasingly competitive marketplace. The right partner can guide you on every step of that journey.

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Works Cited

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