What worked five or ten years ago might now slow your practice down, limit scalability, or even prevent you from taking advantage of automation that could save time and reduce errors. The key is knowing which practices to challenge and how to experiment safely with new solutions.

Identify outdated habits

The first step is taking a hard look at your current workflows. Are there manual steps that everyone does simply because “we’ve always done it this way”? Common examples include manually entering client information across multiple systems, relying heavily on spreadsheets for reporting, or using email chains for approvals and communication. These processes may feel familiar and comfortable, but they can block efficiency and make it difficult to adopt smarter tools.

It’s not about throwing out everything you’ve built. Instead,  ask yourself: is this practice truly adding value, or is it a habit that persists because of comfort or tradition?

Start small with pilots

Once you’ve identified potential bottlenecks, the safest way to explore new technology is through a small pilot. Pick one process that is repetitive, time-consuming, or prone to error, and test a new tool or automation solution there first. For example, if scheduling client appointments takes hours each week, you could pilot an AI-powered scheduling assistant for a single team member or client segment.

Track how much time is saved, how clients respond, and whether errors decrease. Collect feedback from your team about ease of use and potential friction points. A well-structured pilot provides valuable insight without disrupting your entire practice.

Focus on integration

One of the biggest mistakes organisations make when adopting new technology is treating it as a standalone solution. AI or automation tools only reach their full potential when they integrate seamlessly with your existing systems. Consider how data flows between tools, how team members interact with them, and whether the technology supports your established goals rather than creating new complexities.

For instance, implementing an AI tool for document review is less valuable if it requires copying files into a separate system manually. Look for solutions that reduce duplication and allow for smooth handoffs between processes.

Train and empower your team

Technology adoption is a culture change. Even the most sophisticated AI tool fails if your team doesn’t understand how to use it effectively or doesn’t see the value. Build small training sessions into your pilot, and encourage team members to experiment in a low-risk environment. Reward curiosity and recognise improvements, even minor ones, to reinforce a mindset that embraces innovation.

Leadership plays a critical role here. Model openness to trying new tools yourself and celebrate small wins publicly. When your team sees that experimenting with technology is encouraged, adoption becomes much smoother.

Measure, iterate and scale

After the pilot, analyse the results. Did it save time? Reduce errors? Improve client experience? Identify what worked, what didn’t, and why. Then decide whether to scale the solution across your practice or adjust the approach. Iteration is key; rarely does a first attempt capture the full benefit of a new tool.

By running small, thoughtful pilots, your practice can adopt AI and automation safely, gradually replacing outdated “best practices” that may have become barriers. Over time, these small changes compound, creating a more efficient, responsive and future-ready business.

Final thought

The biggest challenge in tech and AI adoption isn’t the tools themselves, it’s mindset. Let go of habits that no longer serve your practice, start small, integrate thoughtfully, empower your team and iterate. By approaching technology as an opportunity rather than a threat, you turn automation and AI from abstract concepts into practical advantages that make your practice smarter and more scalable.

Read more: 25 strategic thinking time questions for firm owners in 2026

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As businesses big and small grapple with ever larger sets of data, they have begun to utilise artificial intelligence (AI) tools to sift through and make sense of the information they have on file.

Employees often have a large number of data sources they use to get things done. One of the problems with having so much data is that it’s not always easy to find what you’re looking for when you need it. For example, a query might arise regarding the firm’s expenses policy, or someone might ask for the latest product documentation for a potential new customer. The problem is that this information often sits in different places.

With all of these different data sources and an increasingly large amount of new data being captured every day, it will only get harder for you to find the policies, documents and files that you need at any given point in time.

Building an internal search engine for your business, using AI tools such as ChatGPT is becoming a popular solution. An internal search engine which can access all your data sources and tools can provide a single place for you to find what you need — whether that’s a concise answer to a well-defined question, a list of images that you used for your last marketing campaign, or the documents you need to fill out your next insurance renewal. An internal search engine is a tool that helps you find what you need when you need it, as long as it’s already available somewhere in the firm.

ChatGPT’s advanced Natural Language Processing (NLP) capabilities enable users to input queries in a conversational manner.
One of the standout features of using ChatGPT is its ability to learn and adapt to individual user preferences. By analysing past interactions and search patterns, the internal search engine can tailor its results to each user’s specific needs, providing a personalised and efficient experience, which can help drive productivity.

Implementing an internal search engine powered by ChatGPT brings multifaceted benefits. It not only accelerates data retrieval, boosting productivity, but also facilitates better decision-making by ensuring employees have quick access to relevant information. Additionally, the system promotes collaboration and knowledge-sharing within the firm, fostering a more joined-up work environment.

Building an internal AI search engine involves integrating ChatGPT (or another similar AI platform) into the existing IT infrastructure. This can be achieved through collaboration with AI development teams or leveraging third-party solutions that incorporate ChatGPT capabilities.

By harnessing this tech, businesses can drive efficiency and harness the power of their data more effectively.

Read more: How generative AI is already changing how we work

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Some of the key trends that businesses will have to navigate this year include economic volatility, the continued importance of environmental sustainability, geopolitical uncertainty and AI moving into the mainstream.

Economic volatility will remain a risk in 2024. The higher interest rate environment will continue to make borrowing expensive for businesses in the short to medium term. Rate cuts are on the horizon but a significant reduction in interest rates in 2024 is unlikely.

The global economy faces the prospect of slow growth this year as businesses and consumers continue to grapple with ongoing cost pressures.

Environmental sustainability is very much on the radar this year. At the COP28 meeting last December, progress was made on the new collective quantified goal (NCQG), which builds on the $100 billion pledged by developed nations to finance climate mitigation and adaptation initiative s in developing nations. Global targets to increase the capacity of renewable energy sources such as wind and solar power were also agreed. Businesses across the world will need to play their part.

Geopolitical uncertainty will remain a key challenge this year due to the upcoming UK general election and the US presidential election. This, combined with the continued war in Ukraine, tension in the Middle East and a slowdown in the Chinese Economy could make for a challenging year.

As AI moves into the mainstream, it will drive efficiencies across various different business sectors and has the potential to turbocharge the digital economy. As AI technology is deployed into real-world uses, it will drive considerable change. Tech companies will benefit hugely from this but the potential for businesses to benefit is very significant in that they can utilise this technology to drive efficiency and increase profit margins.

New tools are already coming on stream, and this is likely to accelerate as the year progresses.

Read more: How generative AI is already changing how we work

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The advent of generative artificial intelligence (AI) has ushered in a new era of efficiency and innovation, fundamentally altering the landscape of how we work. This powerful technology, exemplified by offerings such as Chat GPT, has already begun to revolutionise various industries, reshaping workflows, decision-making processes, and creative endeavours.

One of the most prominent ways generative AI is transforming work is through automation. Mundane, repetitive tasks that once consumed valuable time are now being seamlessly handled by AI algorithms. From data entry to routine customer queries, automation frees up human resources to focus on more complex and strategic aspects of their roles. This not only enhances productivity but also allows for a more strategic allocation of human skills, fostering a work environment that emphasises creativity, problem-solving, and innovation.

Generative AI’s impact extends beyond automation, touching the realms of marketing and decision support. Businesses are leveraging AI for marketing purposes including data analysis and targeting new potential customers.

In decision support, generative AI can act as a powerful tool, processing vast amounts of data to provide insights and recommendations. It can help professionals make more informed decisions by analysing trends, predicting outcomes, and identifying potential risks. As a result, businesses can adapt quickly to changing conditions, mitigate risks, and capitalise on opportunities in real-time.

Collaboration is another facet of work that has been significantly influenced by generative AI. Tools powered by these technologies facilitate seamless communication and collaboration among team members, irrespective of geographical locations. Virtual assistants can schedule meetings, draft emails, and manage routine administrative tasks, enhancing overall team efficiency and enabling a more focused approach to complex projects.

However, it’s crucial to acknowledge the ethical considerations and challenges associated with the widespread adoption of generative AI in the workplace. As AI continues to evolve, addressing issues related to bias, privacy, and accountability will be imperative to ensure a fair and responsible integration into our work environments.

There is also the question of quality – AI doesn’t get it right every time.

Read more: How disruptive innovation can create a new market

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