Is AI Actually Making Your Agency More Profitable?

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Is AI Actually Making Your Agency More Profitable?

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Is AI actually making your agency more profitable, or is it simply adding more tools, processes and experimentation?In this episode of The Fractional CFO Show, Adam Cooper is joined by Emily Hatton, Founder of AI in Agencies, to explore how agency founders and finance leaders can approach artificial intelligence in a more practical, structured and commercially focused way.Emily has spent years working in agency operations, including helping to scale a digital marketing agency before moving into business operations consulting. Today, she helps agencies understand where AI can genuinely improve their businesses, with a focus on processes, efficiency, profitability and measurable outcomes.Rather than starting with the latest AI platform, Emily believes agencies should start by understanding the problem they are trying to solve.That means auditing existing workflows, identifying where teams are spending too much time, finding opportunities to increase output or improve quality, and only then deciding where AI can help.The conversation moves away from generic AI hype and focuses instead on the questions agency leaders and finance teams should really be asking: What are we trying to improve? How will we measure it? What return should we expect? And is the technology actually helping us build a better business?In this episode, we discuss:• Why agencies should start with process, not AI tools – and how understanding existing workflows can reveal where AI can make the biggest difference.• How to audit agency operations for AI opportunities – identifying repetitive tasks, inefficient processes and areas where agencies could increase output or improve client delivery.• Setting measurable goals for AI adoption – whether that's saving time, increasing output, improving quality or achieving a specific commercial outcome.• The risk of AI “anti-productivity” – why unstructured experimentation can create additional work and potentially eat into agency profit margins rather than improve them.• AI and agency profitability – where artificial intelligence can genuinely improve operational efficiency, capacity and profit margins without compromising the quality of client work.• Measuring the ROI of AI investment – and why CFOs, finance directors and agency finance teams have an important role in challenging whether AI spending is delivering a meaningful return.• Why agencies may not need more AI tools – and why getting more value from existing platforms such as ChatGPT or Claude can be more effective than constantly switching to the latest technology.• AI costs and investment decisions – why agency leaders need to understand the commercial return from AI, particularly if subscription and usage costs increase in the future.• AI implementation and change management – why successfully adopting new technology is as much about people, training, processes and culture as the technology itself.• How AI could change agency team structures – including the changing role of junior team members and the growing importance of AI skills, quality assurance and effective prompting.• Why human expertise still matters – how judgement, creativity, quality control and subject matter expertise become even more important when AI can produce information and outputs at speed.• Creating better AI processes across an agency – including documented workflows, guidance on when AI should and shouldn't be used, verified data sources and appropriate checks.A key theme throughout the conversation is that using AI is not the same as improving productivity.If an agency introduces a new AI tool without defining what success looks like, it becomes difficult to know whether the investment has actually saved time, increased capacity, improved client delivery or generated a financial return.For agency founders, CFOs and finance leaders, that means treating AI investment with the same commercial discipline as any other business investment.Rather than simply deciding that an agency needs to “use more AI”, leadership teams need to establish what business problem they are solving, which process they want to improve and what measurable outcome they expect.That could mean reducing time spent on reporting or research, increasing creative output, improving quality or creating more capacity for higher-value client work and new business.For agencies where people are the largest cost base, this distinction matters. Saving time is useful, but what happens to that saved time ultimately determines whether AI creates financial value.This is also where the finance function has an important role to play.A strong CFO or finance director can help leadership teams challenge the assumptions behind AI investment, define the expected return, measure progress and understand whether operational improvements are translating into stronger financial performance.The episode also explores why agencies should be careful about constantly ...

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