There’s no doubt artificial intelligence is transforming the very concept of work and, when combined with effective collaboration, the possibilities are endless. In this six-part blog series, I use my nearly 20 years of industry expertise to dive into these possibilities, imagining a world where AI meets collaboration—and work is never quite the same.

When AI Meets Collab Part 3

In my previous blog, I discussed how mining tribal knowledge within your organization can help you succeed on your projects. We also looked at how using artificial intelligence to do so saves you time on top of helping you build a repeatable workflow that can be optimized for efficiency.

So, how do you decide who should be on your project’s team?

The Cross-Functional Challenge of Collaboration

You walk out of your manager’s office tasked with solving a problem that’s been plaguing your organization. It’s urgent that you build a team to start addressing it, and you know the required expertise doesn’t exist solely in your department; you need to pull in people from around the organization to help.

Chances are, you know what departments they need to come from. Let’s say you need someone from finance, product, operations, marketing and sales. You can check the employee directory for names and contact department heads asking for team members they can spare. Or, maybe you already have contacts in those departments, so you assemble the usual suspects.

Either way, getting everyone you need on a call to kick off your project is another matter altogether.  Depending on where each team member resides in the organization, you might have a one- or two-week lead time before schedules clear up enough. Given the urgency, maybe you can get people to move meetings around, but one person’s urgency is another person’s snipe hunt.

Intelligent Team Selection

Remember when we talked about AI helping us uncover tribal knowledge? The concept of reviewing similar projects completed before the inception of your project comes in handy here. By providing access to those projects, AI can make recommendations for your team based on who participated and what department they represented, provided they are still with the organization. You can also access their contributions to determine if they’d make good additions to your team. If you still have a gap to fill after mining for tribal knowledge, AI can help by providing a list of current employees with relevant skills based on their HR system profile.

With your team now built, AI can scan employee availability using their calendars. If a team member will be on vacation for most of the project, AI can find peers within the same department who have better availability. In addition, AI can provide information on how many projects your team members are currently on,  telling you how much everyone can participate and offer recommendations for less encumbered employees.

Staffing Recommendations

Taking this idea a step further, AI can then alert the project manager that a member of the team has exceeded their ability to work on the project. That triggers a conversation regarding the employee’s priorities, if another team member can fill their role or whether there is sufficient justification for hiring a new employee to meet the demand of the business. 

Because AI can see across the organization, leadership can look at where employees are engaged and make large-scale decisions about resource allocation and how best to achieve business goals. Now, leaders can mitigate the unforeseen consequences of reorganization on projects that are in progress. As decisions are made that affect those projects, AI can restructure team allocation and make new recommendations to project owners to promote effective team collaboration and productivity.

Integration is Key

The secret here is integrations. Recall that to have a complete view of what’s going on, AI must have access to not only the collaboration environment, but also the calendar management tool, HR databases and any other tools used to assess employee skill and availability. By plugging into systems used across the organization, fully contextualized collaboration is possible. If knowledge is power, integration is the key that unlocks it.

Where to Go From Here

With a team roster built and a kick-off meeting planned, it’s time for work to begin. Next, we’ll look at how AI can supercharge the collaboration experience with pop-ups that provide context to the current discussion or access to relevant files based on related published materials. We’ll also look at how reducing information latency can be a lifesaver for project teams that can’t afford rework or delays.

Be Sure To Read These Other Installments In The "When Artificial Intelligence Meets Collaboration" Series.

Part 1: Introduction
Part 2: Uncovering Tribal Knowledge
Part 4: Collaboration Assist
Part 5: Intelligence Everywhere
Part 6: External Intelligence

Ryan Smith

Content Strategist

Known as "The Voice of Mitel," Ryan is a technology evangelist with a unique mix of software development expertise, marketing strategy leadership and professional multimedia development. A lifelong learner, Ryan's passion for storytelling drives his proven ability to simplify complex concepts for audiences around the world.  

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