If the possibilities of AI are too overwhelming, use Google Gemini and start with some basic productivity gains, says Abigail Barnes
Productivity has a new friend, and their name is artificial intelligence!
Let me simplify, demystify, and pull back the curtain on this ‘new kid on the block’ saving you rabbit holes, research time, and jargon overload.
What Is Artificial Intelligence?
AI (artificial intelligence) is a collaborative tool that can learn from data, recognise patterns, help you to make decisions, and so much more. Think of it like a computer brain to your human brain.
Key Milestones in AI Development
AI has been around for a lot longer than most of us realise, and we’ve been using it in our day-to-day work and lives for at least the last twenty years without even knowing.
1956: The Dartmouth Conference, the beginning of AI as an organised field of study; Professor John McCarthy: “Father of AI”
1970s: AI chess-playing computer
1980s: Early consumer AI with “expert systems” used in business and medicine
1990s: AI integrated into software, appearing in spell checkers, grammar checkers, and recommendation systems, enhancing everyday software
2000s: Google uses AI-driven search algorithms and ad targeting; AI enters smartphones with features like predictive text and Siri
2010s: AI goes mainstream with virtual assistants (Siri, Alexa, Google Assistant) becoming common; AI integrates into social media and smart home devices
2020s: AI is embedded in digital life, with personalised recommendations, AI-driven photography, and generative models like GPT
The AI Landscape
To simplify a very complex conversation, I’d like to invite you to think about AI under the following four headings:
1. Predictive AI
Focused on forecasting future outcomes based on historical data, predictive AI uses machine learning algorithms, statistical techniques, and data analysis to identify patterns, trends, and relationships within datasets. By analysing past behaviour and events, predictive AI models can make informed predictions about future occurrences.
Sectors using predictive AI: Finance, marketing, healthcare, manufacture
2. Generative AI
Generative AI is a type of artificial intelligence designed to create new content, such as text, images, music, or videos, based on the data it has been trained on. Generative AI focuses on producing new, original content that mimics the patterns and structures found in the training data it’s been exposed to.
Sectors using generative AI: Content creation, art and design, gaming, research and development
3. Large language models (LLMs)
LLMs are advanced AI models specifically designed to understand, generate, and interact with human language. They are trained on vast amounts of text data, enabling them to perform a wide range of tasks related to natural language processing (NLP), such as answering questions, translating languages, summarising text, and generating content.
Two examples of LLMs: Chat GPT (generative pre-trained transformer), Google BARD (and there are many others)
4. Machine learning (ML)
Machine learning focuses on developing algorithms and models that enable computers to learn from and make decisions or predictions based on data, without being explicitly programmed for each specific task. In other words, instead of being given specific code to perform a task, machine learning models are trained to recognise patterns and relationships in the data, allowing them to improve their performance over time as they are exposed to more data.
Sectors using ML: Healthcare (to detect illness), finance (to detect fraud), marketing (to analyse data), retail (stock management and customer experience)
Three Key Benefits of AI for Executive Support Professionals
- Streamline daily tasks.
- Optimise processes.
- Maximise productivity to increase efficiency.
However, when using AI, you must also consider security, privacy, and the validity of the data. This is a fast-paced, fast-moving field, so invest time in remaining informed. It is also advisable to experiment in collaboration with your IT department.
How to Maximise Your Productivity
Do you ever get to the end of the week and wonder:
- Where did my time go?
- What did I spend time doing?
- Who did I do things for?
- Why, despite all of that, is my to-do list longer than at the beginning of the week?
To find out: Track your time and resources against the questions in the diagram below and create your own weekly analysis report. Let the data you collect support and inform your planning and preparation for the following week.
Once you have this data, you can audit and analyse your time allocation and process when it comes to the tasks you are doing on a daily basis, using the diagram below:
Then, spend some time answering the following questions:
- What tools could help improve my productivity?
- What daily tasks do I want to streamline?
- What new processes do I want to implement?
- What do I need to research/learn/experiment with?
- Who do I need to meet with (executive, IT, operations)?
Now, take your answers and create an action plan like the one in the diagram below, mapping out your responsibilities, tasks, tools you would benefit from, process, and any other resources you require.
Using Google Gemini
Gemini is the AI-powered assistant from Google, integrated into Gmail, Docs, Sheets, and more, with enterprise-grade security and privacy. This is an AI assistant built to assist with a task, not to fulfil an entire job description!
Google Workspace is your virtual office. How would you like to feng shui it and organise it for optimum efficiency?
Google Drive
- Consider how you structure your files.
- Save time by creating workspaces for tasks and projects.
- Share folders to streamline processes.
Google Calendar
- Use the smart scheduling feature to coordinate meetings.
- Try out the Google Tasks feature and app to organise your to-do list.
- Review the Meeting Insights feature to track time allocation.
Gmail
- Check out the AI Smart Compose feature (plus grammar and spell check).
- Try the AI Smart Reply feature.
- Use the mail track feature for confirmation that your emails have been read.
Google Meet
- Caption meetings to foster inclusion.
- Use the AI Transcribe function to save time.
- Take advantage of the noise-cancellation features.
Google Voice Typing
- Speech-to-text can help when someone is driving or walking.
- Try out the Voice Commands feature.
- Coming soon is the real-time translation feature for captions.
Conclusion
Finally, take the data you’ve collected and create a simple dashboard you can use to report to your executive on the performance efficiencies you’ve delivered and the productivity you’ve achieved. Do this regularly (decide the frequency with them).
I can’t wait to hear more about what you try and how things go!
This article is based on Abigail’s session delivered at ES Tech 2024. To view this session, please visit our Learning Library.
