Guessing is not a strategy: How to build decision velocity with AI and real-time data
June 10, 2026 | Live Webinar
Categories: collaboration tools
How much time do you spend doing routine tasks? Just think about how long it takes you to type things like your company name or location details when they get mentioned in an email.
For a long time, Outlook (and I expect other tools) have had autocorrect functions that allow you to type something and have it ‘autocorrect’ to something else. It’s a text expander feature – and you get tools that lay on top of your normal suite of applications that just do text expanding. I even have that function built into my iPad, which is handy when it comes to typing out my email address every time. Now I just type a shortcode and the whole email address populates.
Predictive text takes this one step further by working out what you are going to type before you type it. Predictive apps use passive data, for example, emails, to suggest tasks and updates. Think predictive text when you are trying to type a message on your phone, and scale it up so that the app sends suggestions to your To Do list about what activities you should be working on that day or flags which deliverables are likely to be late because of software defects logged in your testing system.
Many tools are already embedding AI into them to help users have less to do. I was looking at one retrospective meetings management tool the other day and it used AI to automatically name the groupings of sticky notes we created in the meeting, based on the common content of those notes. Clever. It wasn’t always grammatically correct, but it saved us the job of typing a name for each group (although we could edit them if we wanted).
Predictive software sounds like it’s taking the thinking and professional judgement out of being a project manager, but it’s just crunching data for you. For example, you can’t hold information in your head about how accurate each individual team member has been in estimating their workload on this project and the last five projects they have worked on. Predictive software could sift through estimates and actuals, and then flag the three team members with the worst record for getting their estimates right so that you can appropriately challenge them.
This kind of system requires a particular leap of faith as it scours other systems for data. As a community, we’re going to have to go a long way before we are all comfortable with the idea of an app reading our emails and digging through personal files, even if it does predict who isn’t going to hit their deadlines that week.
Whatever collaboration tools you adopt at work, and however you use them, keep in mind that they should be compatible with and reflect what is going on outside the walls of your company. Technology and workplace cultures will continue to evolve and the key is going to be keeping up and staying relevant while making sure your teams have the tools they need to do their jobs productively. That might mean embracing AI and predictive functionalities of tools, even if it feels a teeny bit uncomfortable to do so.
The future is in flatter, more informal working cultures supported by unified organizational collaborative technologies. We might not refer to the tools that way (or even be using the term social and collaborative media) in ten years’ time, but the principles that underpin this revolution in working practices are here to stay.
This article includes a few points that were made in my PMI book: Collaboration Tools for Project Managers. Given what we’ve been going through and seeing so far this year, it felt appropriate to try to pick out some comments on tech for teams and where that might be taking us – because it seems to me that virtual working is here to stay.
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Posted on: December 21, 2020 08:00 AM |
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