Implementing AI with Impact: A Q&A with our CTO, Mark Rotheram

AI levels the playing field for small and medium businesses, but it’s a case of ‘disrupt or be disrupted.’

In this Q&A, our CTO, Mark Rotheram, shares his insights on why artificial intelligence (AI) has become essential for businesses of all sizes, especially small and medium enterprises. He explains how, with AI, there are more opportunities than ever before for small and medium enterprises (SMEs) to “level up” their capabilities with larger enterprises. With AI evolving so rapidly, Mark shares practical advice on where SMEs should start, and common pitfalls to avoid, providing real examples from BCN’s own AI projects.

Q: Why should small and medium enterprises start using AI now, rather than waiting?

The simple reason is that AI technology has never been more capable, accessible or affordable. What we can do today with AI might have cost half a million or a million pounds a decade ago – now it can be done more powerfully and at a fraction of the cost. When you think that historically, only large enterprises could justify those investments, the opportunities for SMEs are vast.

Beyond that, there’s also the (not insignificant) matter of competitive urgency. If you don’t embrace AI, there’s a good chance your competitor will. We often say it’s ‘disrupt or be disrupted’. With AI within easy reach, delaying just gives others a head start.

Q: How do you see AI disrupting traditional business models, especially for smaller companies?

AI has the potential to radically reshape business models. We often challenge our clients to imagine what a startup version of their business would look like if it built itself around today’s AI technology from the ground up. This is your future competition. At BCN, we’ve developed a framework with four levels of AI adoption maturity to help small and medium businesses gauge where they are now and where they need to go. 

Level one: Experiment. Encourage employees to play around with AI tools such as the free AI copilots included in Microsoft 365 to safely explore AI’s capabilities within a secure ‘bubble’ rather than using random online AI and automation services, avoiding data leaks.

Level two: Augment. Many SMEs are now licensing tools like Microsoft 365 Copilot to boost worker efficiency. The key here is to target the right use cases to those who will get the most value.

Level three: Automate. Identify a workflow that’s draining time or resources – that’s often something that’s repetitive or data-intensive – and create a bespoke AI or automation solution to handle it.

Level four: Reimagine. This level has the most profound impact. For businesses whose value is mostly in advice and consultancy, AI can be extremely disruptive. Letting AI handle the heavy cognitive lifting can reinvent how a business delivers value.

Many small and medium businesses start by experimenting, then augmenting existing work. Not every business immediately needs level four; a radical change, but you should at least evaluate and keep an eye on it. After all, ignoring the possibility of an AI-driven competitor could be fatal; sooner or later, every business will need to adapt.

Q: What obstacles are holding SMEs back from using AI in their operations, and how can they overcome these?

The two biggest obstacles for SMEs are usually data, in terms of process readiness, and internal skills.

For AI to work well, you need to have your house in order in terms of processes and data quality. Many small and medium enterprises struggle here. We often walk into a scenario where a company wants to automate a process with AI, but when we examine it, we find no one has ever documented the process clearly and data is scattered across the team in various spreadsheets. AI can certainly streamline workflows, but if you don’t have a consistent process or your data is in disarray, that’s something you’ll need to quickly fix.

The second obstacle is a lack of knowledge or skills, not knowing where to apply AI, or how. SME leaders might be interested in AI but aren’t sure what’s realistic, and employees might not be familiar with these tools. This is totally understandable – AI has exploded so fast. The way to overcome that is through education and some expert guidance. Sometimes it’s as simple as seeing a successful use case. When we show a customer a quick demo – say, an AI summarising a report or handling a customer email automatically – it’s like a lightbulb goes on and they realise the possibilities for their business.

Q: Can you give some examples of SMEs successfully using AI, and what benefits they’ve seen?

For a number of clients, we built an AI-powered shared mailbox management tool. Generic mailboxes with lots of emails, for example, enquiries, complaints, support requests, typically have a team to manually triage and respond to each one. We applied AI to automate that triage and draft responses. The tool reads incoming emails and gauges the sentiment, for example, is it a happy message, or a frustrated complaint?) Urgent or unhappy messages are flagged immediately. Then, importantly, it auto-generates a tailored reply for each email. A human will quickly review that draft and click send, or tweak if needed.

One of our clients saw that their two agents could each save a couple of hours per day, which they could reallocate to phone calls or more complex issues. It’s a big productivity boost without losing the personal touch. This is a really great example of a straightforward win – almost any company with a customer service or support function could use it.

Another example that’s slightly more advanced was our work for a firm that produces financial reports for high-net-worth individuals. It was a very labour-intensive process and analysts could sometimes spend days writing them up. We developed a custom AI solution to automate the bulk of that work. It pulls in the necessary data, uses AI to generate the report text with all the required analyses and personalised details, and then an analyst just reviews and fine-tunes the final document. This shrank the task down to minutes. What’s more, the ROI occurred incredibly fast; the time saved meant the system paid for itself in about two weeks. Everything after that is pure gain.

Q: What are the top risks or pitfalls of implementing AI that SMEs should watch out for?

AI is powerful, but if it’s not used correctly, things can go wrong. Firstly, investing in an AI tool without investing in training staff or integrating the tool into workflows can be a costly mistake if it’s underutilised. AI’s capabilities are evolving monthly, so regular training and change management are critical.

Another issue is data security and governance. There are AI services on the internet that don’t offer a secure environment. Employees who – knowingly or unknowingly – input sensitive client data into them could breach client trust, violate GDPR and data laws, or leak IP. This is a real risk for SMEs, so you need to set clear policies. Use AI tools that are enterprise-approved, train staff on what’s appropriate to share, and consider technical safeguards to block or monitor the use of external AI sites from work systems.

Finally, jumping into AI without a clear goal or expectation is another serious pitfall. Some SMEs get caught up in the AI hype and try to use AI everywhere without asking, “What problem am I solving? What value will this bring?” If you don’t have clarity here, you can waste time and money on AI projects that don’t move the needle.

Q: What strategy should an SME follow to start implementing AI in their business?

I’d recommend a phased, goal-driven approach to any AI implementation. Broadly, you want to align AI efforts with your business objectives and tackle it in manageable steps. Here’s how I often guide SMEs that are starting out to hold a workshop or brainstorming session involving tech people and key business stakeholders to identify where AI might help. List out your pain points, bottlenecks, and opportunities. For example: “Our salespeople spend too much time compiling proposals,” or “Customer service response times are slow.” By surfacing these, you can spot which ones are ripe for an AI solution.

Then, prioritise a quick win. Pick a use case that’s doable quickly and has a visible impact. The ideal pilot project is something that can be delivered in 4-8 weeks and yields a clear benefit (time saved, cost reduced, quality improved, etc.). The reason we push for a quick win first is to build momentum. When others in the company see success, they get more excited and confident about AI.

Treat the first project as a learning experience, then develop a proof-of-concept or pilot and iterate based on feedback. Maybe the AI tool needs fine-tuning, or staff need additional training – incorporate that feedback loop. Next, measure and showcase results: As mentioned, define what success looks like (e.g., “reduce support email backlog by 80%” or “sales reps save five hours a week”) and measure against it. When you hit those targets, publicise it internally to help generate support for further AI projects.

Now that you have one success, expand your AI initiatives. You can tackle a slightly more complex use case next, or deploy the first solution to more departments. Gradually, you develop a roadmap that’s aligned with your business strategy. Over time, you want AI knowledge to spread within the organisation, not just reside with a couple of techies.

Q: How can SMEs bridge the AI skills gap if they don’t have in-house experts?

Partnering with firms like BCN can jump-start your efforts. We often act as an “AI partner guiding companies through the early stages, helping implement solutions, and crucially, we transfer knowledge as we go. That way, your people learn by doing, alongside us. We’ve run engagements where our team comes in a couple days a month to not only build AI features but also to train staff on using them. That external help can compensate for not having full-time AI staff. I’ve seen SMEs evolve from “we know nothing about AI” to “we’re doing it on our own now” in a relatively short period by following this path.

Q: How does BCN support SMEs in their AI journey?

At BCN, we want to help organisations of all sizes implement AI for impact. For SMEs in particular, our approach is very hands-on and tailored. We essentially act as translators between the world of business challenges and the world of AI solutions. We identify a few high-impact use cases, bringing in examples of what we’ve done elsewhere to spark ideas.

Once we pinpoint the opportunities, we help prioritise and create a roadmap. Many clients opt to start with a pilot project, and we’ll help design and implement it end-to-end – whether it’s integrating a ready-made AI service or building a lightweight custom app. Our team are very experiences with Microsoft’s AI stack as it’s reliable and secure, but we’re pragmatic – if the solution calls for something else, we’ll use the right tool for the job. Sometimes we’ll reuse proven templates or components which also saves time and money for customers.

We aim to be a long-term partner to help clients with their roadmap as AI continually evolves. After the first win, what’s next? Can we automate another process, or perhaps look at AI in their product offerings? BCN is there to de-risk and accelerate AI adoption for SMEs. Together, we make sure the AI journey delivers real value and keeps aligning with their goals. Contact us to learn more about BCN’s AI services and how we can assist you in implementing AI for impact.

Read Mark’s full interview with the Business Reporter here.

Mark Rotheram, an AI leader with more than 20 years in the IT industry, became Chief Technology Officer at BCN in 2022. At BCN, he spearheads digital transformation initiatives and drives the company’s AI strategies, focusing on identifying emerging trends and integrating advanced technologies into business operations.