A solo business coach gained 15 hours a week and increased billable time by 40% with just $20 a month in AI tools. The secret? She stopped asking AI to work faster and started using it to think smarter. After releasing my book “The AI Business Accelerator” in January, I’m now sharing more ways to discover the strategic AI advantage that’s transforming businesses today.
Today we’re exploring beyond the hype of the AI Business Revolution to talk about the evolution in AI use that’s happening right here, right now. This article focuses on smart ways to leverage AI for strategic business growth.
After a short break to recalibrate, we’re kicking off Series 3 of our fifth year of the Leveraged Business Podcast, helping consultants, coaches, and business owners create more leverage in their businesses to work smarter, earn more, and achieve sustainable growth.
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ÂFor those joining us for the first time – and I know there’s a lot of business owners who are super AI-curious – let me first quickly explain what we mean by leverage.
Leverage is about multiplying your results without multiplying your effort. It’s the art and science of designing a business that works for you — by aligning your strategy, systems, and strengths to generate greater impact and income, without burning out.
It’s both a mindset and a methodology. A shift from doing all the things to doing the right things well, from hustle to intentional growth.
In practice, leverage shows up through:
- Clear positioning that attracts ideal clients
- Scalable offers that serve at different levels
- Content and systems that build trust while you sleep
- Strategic use of tools and technology (including AI) to streamline delivery and marketing
- Thought leadership that expands your reach without chasing visibility.
Whether you’re a solo consultant, coach, or running a small firm, leverage is what lets you create sustainable success, more spaciousness in your life, and a business model that’s both profitable and purposeful.
Over the past four years, we’ve explored all kinds of strategies for creating leverage from scalable service models, to marketing automation, to organisation and self-care.
Last year, we zoomed in on entrepreneurial resilience, a vital part of what I call the leverage business success dimensions. That journey became the foundation for my book “Rising Resilient” due out later this summer, and it’s packed with insights from the women that I interviewed to help you sustain your focus, energy and joy as you build a business and life that truly align.
But today, we’re diving back into strategic growth – specifically, into a tool that’s dramatically changing how we create leverage. I’m talking, of course, about Artificial Intelligence.
Why focus on AI? Well, after spending most of last year researching and writing The AI Business Accelerator – which hit bestseller lists when it was published in January – I’ve seen firsthand how AI is transforming not just how we work, but how we scale our expertise, serve clients more effectively, and build more sustainable business models around what we do best.
This isn’t about jumping on hype. It’s not just about doing things faster – although there’s a lot to be gained. It’s about doing better work, smarter work, more quality and impactful work. It’s about using AI as a thought partner – not just a tool – and weaving it into the way we think, decide, and deliver.
So in this first episode of Series 3, we’re going to take a big-picture view of where AI is today, how it creates real-world leverage, and how you – as a consultant, coach, or creative business owner – can start using it strategically to grow.
Let’s dive in.
1. Understanding the Current AI Landscape
Let me paint a picture of where we are in the AI revolution. When ChatGPT launched at the end of 2022, it reached 100 million users in just 60 days. That’s faster than any technology platform in history – faster than Facebook, Instagram, TikTok, you name it.
And yet, while it may have felt like AI burst onto the scene overnight, the truth is we’ve been building toward this moment for years. What’s different now is the accessibility and sophistication of these tools, particularly generative AI, which has democratised access to powerful capabilities that were once the domain of tech giants.
AI can help you evolve your business model to achieve next level performance for smarter, faster, sustainable growth.
Here’s a real example. I was working with a small consulting firm last year, helping them streamline their operations. They were spending hours each week writing proposals, creating client reports, and developing training materials. When we first started discussing AI, they were sceptical. “We’re too small for AI,” they said. “That’s for big companies with big budgets.”
Fast forward six months, and they’re using AI tools to handle about 70% of their document creation work. Their proposal writing time has dropped from an average of 6 hours to just 2 hours per proposal, and the quality has actually improved because they’re spending more time on strategy and less on routine writing tasks.
This brings me to an important distinction I want to make about AI and how it creates leverage. We really have two types of AI working together to transform business operations.
First, there’s traditional AI, which creates leverage through automation and analysis. This isn’t just about basic task automation – we’re talking about processing vast amounts of data, identifying complex patterns, and making predictions faster than any human team could manage.
For example, one of my enterprise clients uses AI to analyse customer support tickets across their entire business. The AI doesn’t just categorise issues – it identifies trending problems before they become major issues, predicts seasonal support needs, and even suggests proactive communications to prevent common problems. This kind of analysis would take a team of people weeks to do manually, but their AI system does it in real-time, 24/7.
Then we have generative AI – tools like ChatGPT that create leverage through rapid content creation and scaling of knowledge work. But here’s what’s crucial to understand: it’s not about replacing human creativity; it’s about augmenting it in ways that create exponential returns on your time and expertise.
Let me share a recent example from a marketing agency I used to work with. They would spend about 20 hours per week creating social media content for each client. Now, they use AI to handle the initial content generation, research, and basic optimisation. But here’s the key – they didn’t just automate everything. Instead, they restructured their entire workflow around what I call “AI-human hybrid systems.”
Their AI tools now handle initial market research and trend analysis, first drafts of content, basic SEO optimisation, creation of content variations, and performance analytics. This frees up their creative team to focus on strategic planning, brand voice refinement, creative direction, client relationships, and high-level content strategy.
The results? They’ve reduced their per-client content creation time to 7 hours per week while actually improving quality and engagement metrics. They now serve three times as many clients with the same team and their profit margins have increased by 40%.
But what’s happening underneath that transformation is even more interesting. They’ve moved from a linear workflow to what I call a flywheel system – where AI output feeds insights into content strategy, which feeds performance data back into offer development, creating a continuous cycle of improvement. It’s not just faster – it’s fundamentally smarter.
2. The Strategic Art of AI Prompting
Here’s the part most people miss: the real leverage comes not just from the tool, but from how you communicate with it.
And I’ve worked with tens, if not hundreds of clients on building prompt workflows – not just for AI, but in the past for outsourcing to assistants – workflows that help them break down messy ideas into structured lead magnets, repurpose transcripts into blog articles and social posts, map out onboarding sequences in half the time, and even create role-play scenarios to rehearse sales conversations.
It’s not about asking ChatGPT for “a blog post on my topic.” It’s about structuring the request in a way that leverages the AI’s capabilities while maintaining your unique voice and strategic direction.
That’s why I developed what I call the 5D iSuccess Prompt Framework:
 1. DEFINE
2. DECIDE
3. DESIGN
4. DEVELOP
5. DOUBLE-CHECK
This framework helps you give the AI clear role context, tone, and structure, and guide it step-by-step from idea to implementation.
Let me walk you through how this works in practice.
Recently, I was helping a business coach who was struggling to create consistent content for her newsletter. She’d been asking AI to “write a newsletter about productivity,” and getting generic, uninspiring results.
Using the 5D framework, we transformed her approach.
First, we Defined the context:
“You’re writing for ambitious entrepreneurs who struggle with overwhelm and want practical, actionable advice they can implement immediately.”
Then we Decided on the role and tone: “Write as an experienced business coach who combines empathy with direct, no-nonsense guidance.”
(Obviously, you can build these prompts out with a lot more context than this, but this is just for illustration.)
For Design, we structured the output:
“Create a newsletter with a compelling subject line, a brief story that illustrates the problem, three specific strategies with implementation steps, and a clear call-to-action.”
The Develop phase involved iterating on the output, asking for revisions and refinements.
Finally, Double-Check ensured the content aligned with her brand voice and business goals.
The difference was remarkable. Instead of generic content, she was getting newsletters that sounded like her, addressed her audience’s specific challenges, and generated significantly higher engagement rates. More importantly, what used to take her 3-4 hours of writing time now takes about 45 minutes – but the quality is consistently higher because she’s spending her time on strategic thinking rather than staring at a blank page.
The better your prompt, the higher your leverage. The more context and clarity you put in as you work with the AI, the higher the output quality you’ll get back.
This isn’t just about efficiency – it’s about creating a new form of strategic delegation where you’re partnering with AI to amplify your expertise rather than replace it.
3. Implementation Strategies Across Business Sizes
Now, you might be wondering: that’s great for agencies and coaches, but how does this apply to my specific business? Let me break this down by business size and type, because I’ve seen successful AI implementation across the entire spectrum.
For solopreneurs and small teams of 1-5 people, start with tools that create immediate personal leverage. Another client of mine, a solo business coach, uses AI to create first drafts of blog posts and newsletters, generate personalised follow-up emails, analyse session transcripts for insights, and develop tailored coaching tools. She invested about £200 in AI tools and spent two weeks learning to prompt effectively.
The result? She’s gained 15 hours a week and increased her billable client time by 40%.
But here’s what’s interesting about her approach – she didn’t try to automate everything at once. She started to play and then worked on one area where she felt the most friction: client follow-up emails. These were taking her about 20 minutes each, and I know there are other people that really agonise over it for hours, and she was sending 15 to 20 of these per week. Now, using AI to generate personalised first drafts based on session notes, she cut this down to about 3 minutes per email while actually improving the quality and relevance of her communications.
The success in that one area gave her confidence to expand to other applications. Now she’s using AI to help analyse patterns in her client conversations, identify common challenges that could become new service offerings, and even help her prepare for difficult coaching conversations by role-playing different scenarios.
For mid-sized businesses (6-50 people), the focus should really be on workflow augmentation rather than replacement. A professional services firm I work with implemented AI in three phases, and each phase delivered both time savings and improved profitability. The total cost was less than the salary of one additional employee, but the leverage gained was equivalent to adding 3-4 new team members.
In Phase 1, they automated document processing and basic client communication. This freed up about 10 hours per week across the team. In Phase 2, they implemented AI-enhanced research and analysis tools, which not only saved time but improved the quality of their client deliverables. Phase 3 involved predictive analytics for resource allocation and advanced client insights, which helped them proactively identify opportunities and challenges.
This is a key way for managing your risk and really responding to the changes in the market and the risk environment. The key insight here is that AI implementation isn’t just about efficiency. It’s about designing new workflows that multiply your capacity while protecting, enhancing quality. This firm didn’t just get faster; they got smarter about how they serve clients and how they grow their business.
For large businesses, there’s a lot more you can leverage – all covered in The Leveraged Business Accelerator book and free resources for implementation steps.
4. Building Your AI-Ready Team
Where a lot of businesses seem to hit a wall is not with the technology being the challenge, it’s the human element. I’ve seen companies invest thousands in AI tools only to see them sit unused because no one knew how to integrate them into their daily work. It’s not enough to have the software – you need buy-in, capability, and clarity across your team. And you need leadership.
One 15-person consulting firm I supported had all the tools in place, proposal writers, CRM integrations, analytics, dashboards, but the usage was almost nil. The problem wasn’t resistance to change, it was actually uncertainty about how to use these tools effectively.
So, we implemented a structured rollout that I now use with all my clients. First, we conducted what I call a “Prompt Confidence Audit” to see who was comfortable with different aspects of AI interaction. Then interestingly, we found that the youngest team members weren’t automatically the most AI savvy. Some of the most experienced consultants adapted more quickly because they understood the underlying business processes better.
Then we created tiered training sessions from AI basics to strategic prompt design. But the real breakthrough came when we established AI champions for each department. These weren’t necessarily the most tech savvy people, but rather the ones who were most curious and willing to experiment. They tested use cases, shared results, and became internal advocates for good practice in AI adoption.
Within 90 days usage shot up across the board. Proposal turnaround dropped from three days to six hours. Internal updates got streamlined. Client research became more thorough and faster. But most importantly, the team started seeing AI not as a threat to their expertise or their jobs, but as a co-pilot that amplified their capabilities.
A key lesson here is that AI adoption has to feel empowering, not overwhelming, or worrying. When people understand how these tools can make their work more interesting and impactful, rather than just more efficient, adoption happens naturally. People get excited.
5. Navigating Ethics and Risk Management
A fifth aspect I want to mention is about navigating ethics and risk management, touched on earlier. Of course, with great power comes great responsibility. AI can go wrong quickly if you don’t have the right guardrails in place.
Let me share a story that illustrates why this matters.
A financial services client I worked with started using AI to draft onboarding emails. Sounds simple enough, right? But one phrase in an AI generated email implied a guarantee about investment returns. Something that’s strictly off limits in their industry. Now, fortunately, they caught it before it went out, but it was a wake-up call that AI doesn’t get it right all of the time. And sometimes it fabricates and sometimes it just gets inaccurate facts put in or makes up statistics. So, you really need to be watchful of that. The landscape’s evolving all the time, and I’m sure AI will improve, but at the moment, that’s where we’re at.
So that wake-up call led us to create what I call a lightweight, but actually fairly comprehensive AI ethics policy. And this policy covers data privacy and encryption standards. Transparent use and client consent protocols. Human in the loop quality review processes, absolutely critical, and alignment with regulatory frameworks of those exist in your industry.
And you don’t need a legal department to implement these safeguards effectively. You just need awareness, intention, and a commitment to trust and integrity as you scale. Nothing new there just because of AI. I mean, this is what we do all of the time, but sometimes sense goes out the window when you have a tool that kind of does a whole thing for you. You still need to check it.
The framework we developed includes three key components. First, proactive risk assessment. Before implementing any AI tool, we map out potential risks and put safeguards in place. Second, ongoing monitoring regular checks to ensure AI outputs meet quality and compliance standard. Third, transparent communication, being clear with clients and stakeholders about how and when AI is being used.
One of the interesting things here is that this isn’t something that you would want to give ownership only to the IT department or an IT developer if you have one working in your business. It’s actually more of an HR, more culture change, more of a customer service, customer experience type of area.
So although it falls within risk – risk assurance, if you like – it actually involves people across functional teams, and that’s a big part of the consulting work that we do, is we work very much across processes that involve different departments.
One of the most important aspects of ethical AI use is maintaining human oversight and accountability. Now AI should augment human decision making, not replace it entirely. This means having clear protocols for when human review is required and ensuring that AI recommendations are always subject to human judgment, especially for high stakes decisions, and the people doing those reviews and making those judgements need to be expert enough to be able to do that.
6. Future Trends and Strategic Preparation
Our final segment is really around future trends and strategic preparation. All of the detail about AI, you could get in my book, The AI Business Accelerator. It talks about the evolution as well as the revolution of AI in business. And because the pace of change is accelerating, those who position themselves strategically will have significant advantages.
So, let’s finish with a look at where AI is heading next, because the pace of change is accelerating and those who position themselves strategically will have significant advantages.
Here are three trends I think every entrepreneur should have on their radar. First hyper personalization and scale. We’re moving beyond basic personalization, like using someone’s name in an email to create truly individualized experiences for thousands of customers simultaneously. Now, AI is making it possible to tailor entire customer journeys based on individual preferences, behaviours, and needs. It’s really exciting.
And I’m working with a retail client – I don’t generally work with the retail industry – but they’re testing an AI system that creates individual shopping experiences for each customer. There’s a lot of ideas in there that can come into service-based businesses.
It doesn’t just recommend products. It adjusts pricing, promotions, and even website layout in real time based on individual behaviour patterns. The early results are remarkable. 45% increase in conversion rates and 30% increase in average order value. It’s pretty huge, right?
Second autonomous decision-making systems. Now that might sound a bit scary, but what we’re seeing is tools that can act not just advise. Think CRMs that automatically route leads based on fit scores or analytics dashboards that trigger specific actions when certain conditions are met. A logistics company that one of my partners worked with has implemented AI that makes real time routing decisions for their delivery fleet. Considering traffic, weather, delivery priorities and driver schedules, the system makes thousands of optimisation decisions daily without human intervention, reducing delivery times by 25%, and fuel costs by 18%.
Third: AI ecosystems where multiple tools talk to each other seamlessly. Now, the future isn’t about having one AI tool. It’s about having AI orchestrate your entire [00:26:00] business ecosystem. Imagine AI managing your calendar, your CRM, your project tracker, and your content studio in coordination, creating a truly integrated business operating system. The opportunity here is massive, and those who approach it strategically, not reactively, will come out miles ahead.
The key is to start building these capabilities now, even if you’re starting small with one tiny step. The businesses that thrive in the AI augmented future are gonna be those that begin developing AI literacy and integration of skills today.
7. Wrap-Up & Next Steps
Now, let’s wrap up and bring it back to you. Where in your business could you use more leverage?
Where are you stuck in high effort, low impact work? Where could AI become a collaborator rather than just a shortcut? The transformation we’re seeing isn’t just about technology. It’s about re-imagining what’s possible. When human creativity and strategic thinking are amplified by AI capabilities, it’s about building businesses that are more resilient, more scalable, and more aligned with the work that energizes you most.
To help you start that journey, I’ve created a comprehensive AI implementation toolkit. It’s available free at jayallyson.com/books/the-ai-business-accelerator/. This includes prompt template libraries, implementation checklists, ROI calculators, and a step-by-step guide for building your own custom AI workflows.
So if you go to the Leveraged Business Podcast Episode 124 show notes, you’ll be able to find the link there just to make sure you get to the right place. There’s a whole lot of free stuff there to support what’s covered in The AI Business Accelerator book.
In this series, we’re diving deep into how to use AI in your marketing and lead generation, and I’ll soon be joined by a special guest, Joachim (Joe) Lépine, author of International Bestseller, AI Resilient: How Freelancers and Entrepreneurs Can Thrive, Charge More and Stay Irreplaceable in the Age of AI. And we’ll be exploring how AI is reshaping client expectations, how to position your services for premium pricing, and how to stay one step ahead as the landscape continues evolving.
It’s a powerful, practical conversation and you won’t wanna miss it.
Remember, the goal isn’t to replace human expertise with AI. It’s to amplify what makes you uniquely valuable, while systematically removing the friction that keeps you from operating at your highest level. That’s true leverage.
So until next time: stay smart, stay strategic, and stay leveraged.
Ciao ciao for now.
Note: Figures quoted are calculated by ChatGPT based on ROI conversations with clients
