The relevance of AI in your everyday work

Artificial Intelligence and Microsoft Copilot

Artificial Intelligence (AI) has become an integral part of our daily lives, often in ways we barely notice. From the predictive text on our smartphones to the voice recognition in our cars, AI is quietly revolutionizing how we interact with technology. But how deep does this AI integration go in our work lives, and what does the future hold?

What’s already embedded in our lives

Think about the last time you used face or fingerprint recognition to unlock your device, searched using an image, or asked Siri or Alexa for help.

These are all examples of AI at work. Even seemingly simple tasks like using an app to identify bird calls or plants rely on sophisticated AI algorithms.

In the business world, AI assistants are now commonplace in accounting software and platforms, streamlining operations and improving efficiency.

Not all AI interactions are smooth sailing.

Many of us have experienced the frustration of dealing with robotic voice systems or chatbots when contacting services like HMRC or broadband providers. These experiences highlight that while AI has come a long way, there’s still room for improvement in certain areas.

Are these assistants, platforms and tools really AI?

Currently, all the AI we interact with falls under the category of Narrow AI. This type of AI is designed to perform specific tasks within a limited context. While it can be incredibly powerful within its domain, it lacks the broader understanding and adaptability of human intelligence.

Two theoretical categories of AI remain on the horizon: General AI and Super AI. These concepts, often featured in science fiction, represent AI systems with human-level cognition and beyond. However, they require advancements in supercomputing and quantum technology that are still far from reality.

Categories of AI: Narrow AI (Weak AI) Trained for specific tasks. Examples: Siri, Alexa, chatbots. Cannot perform beyond its task. General AI (Strong AI) Theoretical concept. Human-like intelligence. Can learn and perform any intellectual task. Super AI (Superintelligence) Theoretical. Beyond human capabilities. Thinks, reasons, and learns at an extraordinary level.

Categories and types of AI

The foundation of modern AI lies in vast datasets and complex algorithms developed by data scientists and computer experts. At it’s most simple you can say the programme performs “If This, Then That” logic, a concept that has been around in computing for decades.

AI has made significant strides in fields requiring expert analysis and prediction. From Formula 1 racing strategies to weather forecasting, medical diagnostics, and infrastructure monitoring, AI is proving its worth by processing and analysing data at scales impossible for humans.

The term “Big Data” opened up the commerical potential of AI. Real-time tracking of shipping and flight paths, monitoring celebrities’ private jet usage, and predicting pandemics are just a few examples of how big data and AI are being used to gain insights and make predictions.

Categories of AI: Predictive Analyses data to make predictions about future events or trends. Weather forecasting, stock market analysis, risk assessment. Generative Creates new content or data that is like its training data. Computer graphics, music composition, text writing. Descriptive Analyses data to describe and understand past events. Business intelligence, analytics. Diagnostic Identifies the causes behind past events. Healthcare diagnostics, failure analysis. Prescriptive Provides recommendations on actions to take based on data. Supply chain optimisation, marketing personalisation. Reactive Reacts to its environment in a predefined way without memory. Game playing (e.g., chess, Go). Conscious A theoretical type of AI that would have self-awareness. Not applicable (still theoretical).

Ethical Considerations and Practical Applications

As AI becomes more powerful, questions of ethics and morality come to the forefront. The potential for misuse, as seen in cases like the Cambridge Analytica scandal, highlights the need for responsible development and deployment of AI technologies.

For the average user, the most relevant AI tools might include platforms like Microsoft Copilot, ChatGPT, Grammarly, CodePal, and Claude. These tools can enhance productivity and creativity in various fields.

Every business leader and senior leadership team should be having constructive conversations about the use of AI in their organisation. This includes publishing and educating their people on best practices, what the organistion’s policy and procedures are in using AI platforms – both FREE and paid-for – and working with their people on the best mix of AI, benefits and regulator guidance on data protection and security.

Choosing Microsoft 365 Copilot for your organisation offers a unique blend of advanced AI capabilities and seamless integration with the Microsoft 365 suite.

Unlike other AI platforms, Copilot is designed to work harmoniously with tools you already use, such as Word, Excel, OneDrive, SharePoint and Teams, enhancing productivity without disrupting your workflow. It leverages the power of AI to provide intelligent suggestions, automate routine tasks, and offer insights that drive better decision-making. With Copilot, you get a trusted partner that understands your business needs and helps you achieve more with less effort. It’s not just an AI tool; it’s a comprehensive solution that empowers your team to innovate and excel.

As a Microsoft solution, Copilot provides robust security and access control benefits. Being part of the Microsoft ecosystem, it adheres to the highest security standards, ensuring your data is protected with enterprise-grade security measures. It offers granular access controls, allowing you to manage who has access to what information, thereby safeguarding sensitive data and maintaining compliance with industry regulations.

This level of security and control is often unmatched by third-party AI platforms, making Copilot a reliable and secure choice for your organisation.

The Art of Prompting

Success in using AI often comes down to how you interact with it. Crafting effective prompts – the instructions you give to AI – is key to getting useful results. Just as you might phrase requests differently for Siri versus Alexa, each AI platform may respond best to slightly different prompt styles.

What is a prompt?

It’s the way you ask an AI to help you answer a question or complete a task (it can accomplish).
Success is down to the quality, structure and detail of the prompt.
One prompt can produce different results in different AI tools and platforms.

The best structure for a prompt

Simple direct prompts get simple answers: summarise, explain, find, explore, show.

Track industry news:
“Give me a concise summary of recent news about [Product X].”

Summarise information:
“Write a session abstract of this /[presentation].”

Edit text:
“Check this product launch rationale for inconsistencies.”

Create engaging content:
“Create a value proposition for [Product X].”

Transform documents:
“Create an onboarding presentation based on this /[document].”

Catch-up on missed items:
“What’s the latest on [Project X].”

In Copilot when you use a forward slash / this acts as a trigger to search find attach a file.

The more detailed and complex answers need to construct prompts to nudge the AI to give you the level of answer and content you are after.

The anatomy of a full prompt starts with the Context: give relevant background or context for the action you wish the AI to take.

Improve the answer by giving the AI a role to play: Who or which expert or job role should the AI assume?

Next is the action you wish the AI to take: are they answering a question, providing information, revising existing content or analysing data?

Finally, you can tell the AI how it should output the information – structure copy with headings and bullet points, in a list or table.

Tips for Effective AI Use:

Practice and refine your prompts
Experiment with different AI tools for the same task
Don’t settle for the first answer – ask for alternatives or clarifications
Be polite – some AIs respond better to courteous interactions

For those looking to dive deeper into AI capabilities, especially in a professional context, resources like Microsoft’s Copilot adoption guide and prompt library can be invaluable. Platforms like LinkedIn Learning also offer courses to help you master these new tools.

As organisations continue to navigate this AI-enhanced world, staying informed and adaptable is key. Whether you’re a tech enthusiast or a casual user, understanding the basics of AI and how to interact with it effectively can open up new possibilities in both personal and professional spheres.