AI Powering Your Product Team

Introducing a 6-part Blog Series

Invoke has been working on AI projects in image processing, social text semantics and generative applications. As we’ve built familiarity with machine learning and related technologies, we’ve also been paying attention to AI powered tools that aim to boost productivity in daily workflows. In this 6-part blog series, we want to share some of our team’s learnings on using AI in their work.

Changing Perspective on AI

The way we think about artificial intelligence has come a long way since the explosion of generative models in early 2023. Although large language models still have an aura of mystery and wonder, the belief that they are magical problem-solving tools has gradually given way to a more practical reality as we wrap up the year.

Recent months have seen growing awareness of critical issues stemming from AI, including bias arising from opinionated training data, ethical dilemmas, hallucinations in generated content, data privacy concerns, and debates over ownership and copyright of AI-generated material. So does this mean we will soon see the end of the AI craze? Unlikely. But understanding the limitations and pitfalls of generative models can help us identify when they can be used effectively and when it’s best not to use them. The era of AI isn’t on the decline, we’re just learning to employ AI more responsibly as opposed to earlier in the year when the excitement and novelty around it often overshadowed the need for careful consideration. It remains clear that incorporating AI in daily workflows can be a valuable time saver and productivity booster, as long as it is used for the right tasks and in the right context.

People can be Reluctant to Adopt AI Tools

This shouldn’t come as a surprise, but not everyone is excited about using AI technology and it could be for a variety of reasons. We wanted to know how our team at Invoke felt about it, so prior to our annual company off-site event in the summer, we surveyed employees on what contact they’ve had with generative AI and what barriers might be preventing them from using it more.

Firstly, we found that across all disciplines, most have at least experimented with using ChatGPT, but haven’t delved much into other, perhaps more specialised tools. It made sense that ChatGPT was the first point of contact for many since it’s meant to be very general purpose and requires no setup other than creating an account. In terms of reasons not to try other tools, here are the top three that came up, along with our suggestions on how to mitigate them:

No time to learn to use new tools — it may seem like an unnecessary time investment at first glance, but if it helps improve efficiency in the longer term, the net result could very well be in your favour. Consider looking for tools that integrate into your existing software, like Figma and VSCode plugins, to lower some of the novelty barriers.

AI hasn’t earned enough trust — A good way to look at generative AI is as a first step to get you started towards completing a task. It won’t and shouldn’t take you all the way there, but rather provide inspiration or a solid starting point to work from. That way you don’t have to trust it to be perfect.

AI tools are behind paywalls — It can be deterring to have to pay for a tool you aren’t sure will save you time. Free or low fee trials are often available though, which helps. Additionally, if you’re lucky enough that your company offers a professional development budget, learning to work with AI could count towards it.

What to Look for in an AI Powered Tool

At Invoke, we have been actively exploring AI-powered tools to streamline our processes across all our disciplines: design, technology, operations, strategy, and project management. During the company off-site we suggested a selection of productivity-enhancing tools in every category. As we were compiling this list of tools, we’ve identified what you should be considering when deciding which ones are worth the time and effort to test in your workflow.

Here are the key things we looked for:

• Compatibility, setup and learning curve: we looked for tools that integrate into existing workflows with minimal setup and are easy and intuitive to use. Plugins for popular existing software are a good example since they don’t require adopting a whole new application.
• Quality of suggestions: it’s important the tool provides relevant suggestions. We don’t expect AI to give us perfect answers to be used as they are, but they should serve as a strong foundation for inspiration and further refinement.
• Pricing: an important facet, especially for users that aren’t sure if AI can help them be more productive. Having tiered pricing or a free trial allows us to evaluate if the tool meets our needs without committing too much upfront.
• Ethical AI and privacy: especially with recent growing concerns, how the tool handles data privacy and ethical considerations is important to maintain user trust and avoid legal issues.

Next — Our Team’s Experiences

Fast forwarding from July to November, as 2023 is starting to wrap up, we’ve been checking in with our team members from each discipline at Invoke to gain insights into how they’ve found using the suggested tools and how they’ve been introducing AI in their workflows in general.

We’re excited to present “AI Powering Your Product Team”, our 6-part blog series that casts a look at the year of generative AI through Invoke’ team members’ stories of learning to use new intelligent tools in their daily work.

Nov 21 — AI-Powered Product Design
Nov 28 — Redefining Software Development Efficiency
Dec 5 — Optimizing Project Management with AI
Dec 12 — Breaking My Resistance to AI
Dec 19 — AI Text-Generation Tools, Today and Tomorrow

Shoutout to Robbie Sebullen — previous senior designer, moved on to an AI startup Cognosys — who was a part of this preparation and presentation.