Generative AI in Business
In this episode of The Bottom Line, we sit down with Darwin, Founder of Pathfinder—an AI consultancy helping organisations translate emerging technology into measurable outcomes. With experience spanning enterprise clients and fast-growing teams, Pathfinder focuses on a simple but critical objective: helping businesses move beyond experimentation and start achieving real results with AI.
The conversation explores how generative AI is reshaping business operations, particularly for leaders who are aware of the technology but are still working through how to apply it in a meaningful, practical way.
From Awareness to Application
Most businesses are no longer asking whether AI is relevant. That question has already been answered. The challenge now lies in understanding how to use it effectively.
There is a clear pattern emerging in how organisations approach AI:
Initial uncertainty about whether the technology is real or overhyped
Rapid exposure to tools and use cases
A sense of overwhelm due to the pace of change
A need to translate capability into tangible outcomes
The businesses that progress are the ones that move quickly through this cycle and focus on implementation. They treat AI as part of their operating model rather than an isolated experiment.
Thinking of AI as an Extension of Your Team
One of the more practical ways to understand generative AI is to view it as an extension of your team.
Rather than thinking in terms of software, it can be helpful to think in terms of capability. In the discussion, AI is framed across three distinct roles:
The Assistant — supports research, summarisation, and general tasks
The Thinker — provides structured analysis, problem-solving, and recommendations
The Creator — produces content across written, visual, and audio formats
This framing simplifies how businesses engage with AI. It becomes less about tools and more about how additional “capacity” can support decision-making and execution.
Platforms such as ChatGPT and Microsoft Copilot sit at the centre of this capability, offering flexibility across all three roles depending on how they are used.
The Untapped Power of Off-the-Shelf Tools
A key insight from the episode is how much value already exists within off-the-shelf AI tools.
There is often an assumption that meaningful results require complex builds or custom software. In reality, many businesses are achieving significant outcomes using tools that are readily available today.
A practical example shared highlights a mid-sized real estate agency that implemented a small number of tools and quickly transformed parts of their operations. Within a short period, they were able to:
Translate key documents into multiple languages
Automate routine communications with clients
Produce branded marketing materials at scale
Generate AI-led video updates with minimal manual input
The shift did not come from building new technology. It came from using existing tools more effectively.
Why Progress Often Stalls
Despite the availability of these tools, many businesses struggle to move forward. This typically comes down to two factors:
Lack of inspiration — not knowing where AI fits within the business
Lack of capability — not knowing how to use the tools effectively
Addressing these gaps requires a shift in how AI is approached. Instead of treating it as a task-based tool, leading businesses are using it to enhance thinking, challenge assumptions, and improve decision-making.
A simple but powerful approach discussed in the episode is asking AI to guide the process itself. For example, prompting it to “interview you” about your business goals and priorities can significantly improve the quality of outputs. It creates a more structured and useful interaction, particularly for those still developing their confidence with the technology.
Elevating Decision-Making With AI
Beyond efficiency, one of the most valuable applications of AI is in decision-making.
Rather than focusing solely on automation, businesses are using AI to gain deeper insights into their operations. This includes reviewing activity, identifying patterns, and highlighting areas for improvement.
An example shared involves analysing past emails, meetings, and workflows to assess whether daily activity aligns with broader business goals. When prompted correctly, AI can provide structured feedback on:
Where time is being spent
Whether actions align with priorities
Opportunities to improve performance
To get meaningful insights, it is important to actively ask for critical feedback. AI will often default to supportive responses unless prompted to identify gaps or areas for improvement.
Automation: Where It Stands Today
Automation is one of the most discussed aspects of AI, but also one of the most misunderstood.
The current landscape can be broken into three stages:
Understanding context — AI can access and interpret your data
Assisting with tasks — AI drafts outputs for review
Taking action — AI begins executing tasks on your behalf
The third stage is now emerging. With integrations and connectors, tools such as ChatGPT and Microsoft Copilot are starting to move beyond assistance and into action.
Even without full automation, there is immediate value in simple, repeatable workflows such as:
Weekly account or client briefings
Competitor and industry updates
Meeting preparation summaries
These small automations create consistency and free up time for higher-value work.
Structuring AI Through Agents
As businesses become more advanced in their use of AI, the concept of “agents” becomes increasingly relevant.
An AI agent can be thought of as a specialised role within your digital environment. It is configured with a specific purpose, set of instructions, and access to relevant information.
Common examples include:
A marketing agent aligned to brand tone and messaging
A compliance agent ensuring regulatory requirements are met
A sales agent providing account insights and preparation
Separating these roles allows for greater control and consistency. It also mirrors how teams operate in a traditional business setting, making it easier to integrate AI into existing workflows.
Rethinking How Work Gets Done
One of the more important themes in the discussion is that AI does not simply enhance existing processes—it often requires them to be rethought.
Certain workflows that are intuitive for people are not always suited to AI. At the same time, AI excels in areas that may not have been prioritised before, such as structured analysis or dynamic outputs.
This shift presents an opportunity. Businesses that are willing to adjust how they work—not just what tools they use—are better positioned to unlock the full value of AI.
Developing the Right Mindset, Skill Set, and Tool Set
To use AI effectively, businesses need to focus on three core areas:
Mindset — openness to experimentation and new ways of working
Skill set — becoming confident, capable users of the technology
Tool set — selecting and integrating the right platforms
In practice, this often means using a combination of tools. Platforms such as Claude, Google Gemini, and ElevenLabs each offer different strengths across writing, multimedia, and voice applications.
The goal is not to use everything, but to build a stack that aligns with how your business operates.
Looking Ahead
AI is evolving quickly, but the fundamentals remain grounded in practical application.
Businesses that focus on clarity, structure, and consistent use will see the greatest benefits. Those that delay adoption risk falling behind—not due to lack of access, but due to lack of implementation. For business owners, the opportunity is clear: start small, build capability, and expand over time.
Listen to the full episode of The Bottom Line to explore how businesses are practically applying AI, and how you can start building capability within your own organisation.