What Is In Our Chief AI Officer’s Toolkit

A Chief AI Officer’s Toolkit in Workday Optimisation

Generative AI has rapidly emerged as a transformative force within the professional landscape, offering unprecedented efficiency and innovation across various industries. Since OpenAI hit the scene with ChatGPT in November 2022, countless new AI businesses have sprung up, offering all sorts of tools that promise to save us time and effort.

But what is the real extent of GenAI’s ability to help us out at work? What are the risks of doing so, with a relatively new and unexplored technology? What are the quality tools, and what is just riding the AI wave?  

Introducing Darshna Shah from Elastacloud

Who better to advise than Darshna Shah from Elastacloud, our latest acquisition in the Data and AI space. She’s one of the few to proudly wear one of the newest and most exciting job titles on the scene: Chief AI Officer. AI is her bread and butter, her 9-5, and her passion of the past decade.

With over 10 years specialising in Data Science, Darshna has seen the rise and fall of technology trends. An established speaker and mentor, Darshna’s passion for Data started during her PhD in Neuroscience. At Elastacloud, she leads the strategic development of AI solutions across industries. Giving us a peek behind the curtain to how some of these technologies function, Darsha will take us through the top priorities when using Gen AI at work into a Chief AI Officer’s Toolkit, and let us in on the tools she herself uses to make her day that little bit easier.

Knowing the Limits of GenAI

The hype around Generative AI certainly isn’t unfounded, but there are misconceptions around what Gen AI is realistically able to handle better than us humans. “So many people think that AI solutions are plug-and-play, that the ‘intelligence’ behind them can do almost anything.

While advancements are being made every day in what we’re able to achieve, we have to remember this is still relatively new technology,” says Darshna. “AI is only as useful as the data you feed in, and most people don’t realise the time that goes into making data understandable and useable by humans, let alone computers. For the most complex and valuable AI solutions, the work of Data Scientists is still vitally important.”

Generative AI can help us predominantly in Knowledge Work, but it still takes a lot of time and energy from AI engineers to allow this to happen. Once the solution is ready and in the hands of the user, there are further issues to consider.

Security, Responsibility and Best Practice

As businesses increasingly harness its potential, it’s crucial to balance the benefits and potential pitfalls of Artificial Intelligence, and approach these tools with a conscientious mindset regarding security and ethics.

“Often our customers’ biggest concern is the safeguarding of sensitive data. Employees have to be careful about inputting confidential information into public Gen AI platforms,” Darsha warns. “Microsoft’s Azure OpenAI Service are very open about the how they use your data, which gives customers confidence.”

Public tools may not have stringent data privacy measures in place, risking exposure or misuse of sensitive information. For example, customer details, financial records, or commercial business strategies should never be fed into these tools without a comprehensive understanding of the associated risks.

“It’s also really important that companies are clear about how they allow employees to use AI-generated content,” Darshna adds. “Outputs should be ethical and free from bias, and often that means knowing to scrutinise AI suggestions critically to prevent misinformation.” So taking on the limitations and privacy considerations, what are Darshna’s favourite tools to use responsibly during her work day?

A Chief AI Officer’s Toolkit

Langchain

Langchain offers robust solutions for crafting and visualising complex conversations using natural language processing (NLP). For businesses aiming to develop chatbots, conversational agents, or any form of automated dialogue system, these tools are invaluable. “In my work, Langchain and Langraph are the tools getting technologists excited,” says Darshna. “We’ve been experimenting for a while and its been so exciting to start using them in customer projects. Anyone who wants to start building their own solutions needs to try them out.”

Co-Pilot

Microsoft Copilot integrates seamlessly with Microsoft 365, leveraging AI to assist with writing, data analysis, and summarisation tasks within Word, Excel, Outlook and more. Darshna: “As simple as it may seem, Co-Pilot’s auto transcription and summarisation native within Teams meetings is a lifesaver when your diary is as busy as mine. Taking notes and writing down next steps is something I really value to stay organised and on top of my day, but it’s a task that can quickly get away from you when you’re back-to-back.”

Jetbrains

Jetbrains’ suite of tools enhances software development by providing intelligent code completion, error detection, and insightful suggestions directly within the integrated development environment. Darshna: “I don’t get a load of time to code these days, but when I do, Jetbrains is a lifesaver. It just takes care of those annoying little tasks that can stall your flow.”

Whimsical

Whimsical empowers teams with capabilities to create mind maps, flowcharts, wireframes, and sticky notes using AI-driven suggestions, enhancing ideation and planning processes. “I find so many of the free flowchart and visualisation tools so frustrating to use,” Darshna says, “so this just takes away a lot of the aggro. I know a load of people across departments at Elastacloud are big fans.”  

ChatGPT

ChatGPT might seem like the obvious answer, but OpenAI’s LLM is at the core of all of the most popular Gen AI solutions and applications, so why not go straight to the source for some peace of mind? Darshna: “I still use it really often to check over writing and code. I feel like ChatGPT is just a part of everyday life now, and its model is only getting better and better. But of course it is a public tool, so I’m always careful about what I input.”

The Final Word

The incorporation of generative AI tools into the workplace signifies a paradigm shift towards enhanced productivity and innovation. However, it’s imperative to weigh the advantages against potential risks; appropriate training, data privacy measures, and ethical considerations will ensure these powerful tools are used responsibly and effectively by everyone within a business.

Crucially, according to Darshna, for the real problems, it pays to go bespoke: “I still see companies investing massively in out-of-the-box Generative AI solutions, not realising the inherent limitations. They do this because they don’t have the internal Data Science talent – there is a skills gap widening faster as AI technology develops.”

“Most of the problems that could help save the most time and energy within businesses are complex and hyper specific to the company. In many instances, traditional Machine Learning techniques could address what they’re looking to solve quicker and easier, but the talent just isn’t there to recognise that and fill the demand.”

“Free online tools will save you time, but for proper business transformation, there’s no substitute for consulting Data Scientists to solve the specific problems that will truly speed up processes and save your time and sanity.”

Interested in learning more about AI following our Chief AI Officer’s Toolkit? Darshna runs the Data Science London Meetup Group, the biggest community of Data Scientists in London, sponsored by Acora and Elastacloud.