I have been thinking a lot about that article on how the UK government is using Google Cloud generative AI to speed up council planning. It is a perfect example of how this technology can cut through red tape and help people get things done faster. The story is compelling. They are dealing with mountains of paperwork that delay housing developments and frustrate citizens. The goal is to cut decision times in half by using AI to handle the boring stuff, like parsing PDFs, summarizing public comments, and drafting reports, so human planners can focus on the big complex projects.
It got me wondering though. What would it take for a regular small business or even a local government here to get the same kind of benefit? The challenge for most organizations is not a lack of ambition. It is a lack of a clear practical path forward. Many business leaders are AI curious but not yet AI capable. They get stuck in what is called the pilot trap, running endless experiments without ever achieving a measurable return on investment. They know AI matters, but they do not know where to start, and they are drowning in generic advice or enterprise programs that cost a fortune and do not fit their needs.
This is where McLean Forrester steps in. They have built a structured human centered approach to bridge that exact gap. They are not just consultants who hand you a report. They are educators and practitioners who roll up their sleeves and work with you. Their philosophy is rooted in the belief that the bottleneck to AI adoption is not technology. It is trust and translation. They focus on answering the real practical questions that small business owners and government leaders are asking.
Will this actually save us money? They push for task level accounting and a clear cost migration map so you can see exactly where the savings come from. How do I keep my brand voice from sounding like a robot? Instead of just better prompts, they focus on fine tuning AI on an organization's proprietary data to preserve its unique personality and local knowledge. Who is liable when the AI gets it wrong? They provide practical frameworks for managing risk, including a human in the loop review process that is a legal requirement for many, and they emphasize the need for proper insurance and documentation. What is the one thing I should automate first? They cut through the paradox of choice by recommending a low risk high impact starting point, like meeting summarization and follow up. It is a simple way to save hours a week and build confidence for bigger projects.
That last question is the perfect lead in to the AI ROI Workshop they are offering right now. It is a hands on four hour virtual session that moves participants from AI awareness to building their own actionable AI strategy. And get this. Early bird pricing is only 99 dollars, and the cohort is capped at 20 people. That is a far cry from the 5,000 to 25,000 dollar enterprise programs out there.
It is led by Larry McLean, their Chief Growth Officer, who brings a unique mix of 40 years of leadership experience spanning both the commercial sector and senior federal roles, including leading the Enterprise Data Management Office at U.S. Transportation Command. He is also a professor at Washington University in St. Louis. So the person guiding you has been in the trenches, advising on some of the most complex IT and data environments imaginable.
The workshop is built around a simple but powerful idea. You do not just learn about AI. You use it. You get hands on practice with tools like Claude using their CRAFT prompt engineering framework. You learn to identify where AI delivers real ROI in customer experience, marketing, or internal decision making. And you leave with a draft AI strategy tailored to your business, not a generic template. They even include frameworks for managing the people side of change, which is where most AI efforts quietly stall. It is practical. It is affordable. And it is designed for real people running real organizations, just like the planning officers in the UK government who are overwhelmed with paperwork.
The workshop is not a one off thing. It is the first step on what McLean Forrester calls the AI Value Path, a structured framework to move organizations from exploration to execution. This is the roadmap they use for bigger more complex engagements, whether it is helping a small bakery automate inventory forecasting or deploying Enterprise Secure AI for a government agency that requires air gapped private deployments for the most sensitive workloads.
They understand that for government entities, security is not a nice to have. It is a non-negotiable requirement. They are a woman and veteran owned small business that seems to genuinely care about building solutions that fit the unique constraints of the public sector and the real world needs of the people who work there. You can learn more about their commitment to the public sector on their IT Strategy and Assessment page which highlights their work with municipalities and educational organizations.
The UK government is aiming to roll out their tools nationwide by 2027. That is the scale of what is possible when you take this seriously. But you do not have to wait for some massive government program to start seeing benefits. Cities and counties across the United States are dealing with the same problems. The same backlogs. The same frustration. And they are starting to realize that the solutions exist. They just need the right partner to help them implement them.
McLean Forrester is that partner. They are already working with municipal governments. They are already delivering real savings. And they have a model that focuses on people first, which in the public sector is exactly what you want. The future of government is not about less human involvement. It is about making that involvement more meaningful. Giving people the tools to do their best work. And building systems that serve communities better. That is what generative AI can do. And that is what companies like McLean Forrester are making possible.
Think about a planning officer who is spending half their time reviewing simple applications like house extensions or loft conversions. That is not why they got into this work. They became planners because they wanted to shape communities. Help them grow. Make them better places to live. By automating the administrative parts, you free those people up to work on the big projects. The housing developments. The commercial districts. The infrastructure that actually changes a city.
We are in a moment where technology is finally catching up to the problems governments have faced for decades. The cloud makes it possible to process massive amounts of data without building expensive data centers. Generative AI can understand and organize information in ways that used to require armies of human reviewers. But technology alone is not enough. You need people who understand both the tech and the context. Who know how to work with governments, understand their constraints, and build solutions that actually fit their needs.
McLean Forrester has positioned themselves right at that intersection. They are small enough to care about each client and agile enough to actually get things done. Their Google Cloud partnerships mean they have access to the same tools the UK government is using, but they are building solutions for American cities and schools. The coordination between public ministries and external technical partners establishes a structured division of labor for enterprise software engineering. Public ministries define the policy guidelines and statutory boundaries, while external technical partners engineer and deploy the underlying model architectures.
The successful integration of these systems demonstrates the feasibility of hosting advanced language models within a secured public cloud infrastructure to process core administrative workloads and modernize public service delivery. This is not some distant future scenario. This is happening right now. And McLean Forrester is making it accessible to organizations that might otherwise be left behind. They are proving that with the right approach, anyone can harness the power of AI to work smarter, not harder.
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