There are several AI tools that can help you save time. However, the bigger question is, “Where can I use AI to save myself a tangible amount of time without creating new work?” The truth is that the AI tool itself will not help you save time, but how well it can be implemented into repetitive tasks.

Research has shown that, on average, users of AI tools are saving 3 hours a week. The biggest gain was found in users who are using AI tools to help generate/ debug code, saving nearly 8 hours a week. Other research suggests that staff are saving around 3-5 hours a week. However, this can only truly translate into business value if the time is being reinvested into higher-quality work.

This guide will provide an overview of real-world use cases for AI tools that can save you time. We will look at examples of how simple they can be to set up, the recommended process to follow, and example prompts.

​

AI tools can help you save time with specific tasks, whether it be drafting, summarising, searching, categorising, data extraction, coding or answering simple queries. However, if the tasks are repetitive and rule-based, then you can save hours of manual work. However, if there is some judgement or responsibility involved, or there is missing context, then you may create additional review work.

Research shows that there can be large variations in the time saved by using generative AI in the workplace depending on the complexity of the task, expertise of the user and how well it fits into the workflow. For example, whilst your AI assistant may be great at giving you a draft, it may not be so great at deciding if it is suitable for a regulated customer communication.

The most reliable way to save time is to have a simple process. Identify what repetitive task you have. What is the input? What is the output? Can we use AI to get a draft? Have a review process in place for any accuracy/compliance issues. This will prevent “AI sprawl” where you may use multiple tools, but still have to spend a lot of time reviewing, correcting and prompting.

​

Time-saving with the help of AI can be done through writing. This includes emails, meetings, updates, proposals, documents, responses to customers, etc. An AI writer is perfect when you know what to write but need a little help with it.

For example, if you are a project manager and need to write a weekly update. You can copy and paste your notes into an AI assistant to give you a concise update with separate sections for risks, decisions and next steps. Whilst you will still review the facts, the time saved on writing can be dramatic.

“Write me a concise weekly update from the following project notes. Please keep paragraphs short. Please include details on progress, key decisions, risks and next steps. Do not include any information that isn’t included in the notes. Please keep it professional.”

As the input is known and the output is predictable, this is a great use case. AI can save time by improving wording and formatting. These tools work best for creating rough drafts, refining language, summarising content, outlining ideas, and responding to common customer enquiries. However, complex announcements, legal documents, and technical writing often require human expertise and careful review.

​

AI tools can help you save time by providing searchable meeting notes. Whether it be transcription, summarising, action items or intelligent search. This is a great tool to have for remote teams, customer-facing teams or teams with a lot of recurring meetings.

For example, if your team are doing client discovery calls, you can get a summary from your AI meeting assistant. This will surface any objections, actions, and commitments. This will enable your consultant to save time spent on remembering the discussions held and instead focus on formulating an effective proposal.

Make sure that the AI is helping you become an active listener. The AI will not know about the political situation, the underlying fears, or the difference between a comment and a commitment. It is important for you to use the AI summary as a base. Make sure to assign an owner to ensure everything is accurate.

Prompt example

“Please summarise the meeting notes below. Please include details on decisions, questions, action items with owners and deadlines and any customer concerns. Highlight any statements that need verifying.”

​

One of the most obvious areas to use AI tools to save you time is in software development. You can use them to help generate code, explain code, create test skeletons, help debug, create documentation and help with migrations. Research has shown that developers using GitHub Copilot completed a controlled task to create an HTTP server in JavaScript 55% faster. A larger study showed that engineers completed more pull requests during the weeks when they had the most use of their AI assistant. However, at extremely high usage levels, the return was reduced.

The biggest gains you can get from using AI as a developer are not from asking for the whole application to be created, but instead focusing on a specific function, test, refactor or error.

As a developer, you can copy and paste your stack trace, code and recent changes into an AI coding assistant. A useful prompt would be;

“Please provide me with the most likely cause of the issue. Explain why you think this is the cause. Provide me with a suggested fix (keep it to the minimum). What edge cases or tests should I add? Do not make up any APIs or assumptions.”

This will save you time as you are using the AI as a debugging tool. You still need to validate the fix, run tests and check for any security concerns.

You can also use AI to help with other automation tasks. For example, creating release notes from merged pull requests, summarising incident timescales, creating runbooks and converting customer issues into bugs. These are repetitive tasks that can be automated but still require engineering review.

​

Using an AI research assistant would enable you to save time because the assistant helps you compile all the information that took hours to research into a summary. It can be used to conduct competitive research, market summaries, policy changes, technical comparisons, and internal discoveries. Make sure that you request sources and distinguish between facts and assumptions.

For example, when you are doing research on new integrations for your product team, you can instruct your AI research assistant to make comparisons among the available options. This is supposed to cover the cost, security, level of difficulty of integration, and the quality of support offered. After your research, you need to validate the information from the vendor and reference people.

“Research the options currently available for [task]. Compare each option based on ease of implementation, security, scalability, and overall cost. Support factual claims with reliable sources and include citations for all sources used. Conclude with a summary of the key differences and a recommendation based on the findings. Separate facts from assumptions.

This will help you to get the most out of your AI by forcing you to be structured, evidence-based, and transparent. This will reduce the risk of confidently stating something that has no evidence.

​

However, not all AI possibilities are worth pursuing. Those that are easy to implement and deliver value are the summarisation of meetings, writing of emails, summarisation of documents, programming help and internal knowledge search.

Medium effort tasks include customer support drafting, CRM data enhancement, automated reporting and developer automation. These will need better-defined rules, controls and data quality checks. Examples of high-effort activities would be full automation, custom-built AI assistants, document extraction and AI in core business systems. These would deliver great benefits but would need some process design, testing, governance, security checks, and change management.

Begin with an easy activity that is repetitive, easily reviewable and low-risk. Once you have established a good workflow, you can scale up.

​

Start with one process. Identify a repetitive process that takes a few hours a week to do. Time how long it takes currently and use AI on just one part of the process to see the impact.

Do not make your prompts vague. Vague prompts will result in vague responses. Some of the elements that should be included in a good prompt include: The role you want, the target audience, the format you need, limitations, sources, and what needs to be reviewed.

Ownership. Even though AI can assist in the process of drafting, summarising, categorising, and suggesting, it is necessary to make sure that human beings own the decisions and approvals. This may be in areas such as finance, healthcare, legal, security and HR.

Build up a bank of prompts. The more often you can use your prompts, the more time you will save. Save your prompts after they are approved by you and reuse them for status reports, meeting minutes, code review comments, customer replies and research summaries.

Be honest about the time saved. How long did the task take before you started using AI, and how long does it take now? How much time do you spend reviewing and refining the AI-generated output?  If you are saving time on the drafting but spending more time correcting, then you will need to adapt your workflow or improve your prompt.

​

We can help you identify where you can use AI tools to save time within your organisation. As an AI consulting company, our team will help you determine which processes can benefit from AI technologies. In addition, we can support you in making your data ready, creating the proper integration strategy and implementing governance to make sure that you get the most out of the automation process.

We don’t sell products or software; we provide professional services tailored to your needs. Our team works closely with you to select, implement, and optimise the right solution for your existing systems. Successful implementation of AI tools does not consist of introducing yet another application. It all comes down to making sure that you have the right blend of everything.

Whether you need automation for developers, AI for customer operations, to assess your workflows or have a practical plan in place to adopt AI, we will ensure you get real results. Less manual work, better decision-making, and more time on high-value work.

​

AI tools that save time are most effective when they are solving a specific and repetitive problem. The best results will be achieved from having focused workflows. Let AI handle the drafting, while people review the content. When it comes to summarising information, humans make the final decisions. Similarly, AI can suggest code, but engineers must validate it.There is evidence to show you can save a tangible amount of time using AI. Particularly with writing, meetings, research and software development. However, this should be carefully managed.

Start with one process. Be clear on what success looks like.Create a library of prompts you can reuse.Be honest about how much time you are saving. If you would like expert guidance on identifying opportunities, designing responsible workflows and implementing practical automation, then get in touch with Nexotechsoft.