AI, or artificial intelligence, is making its way into all types of business processes. Leveraging AI can help a business grow more efficiently while sometimes saving time and often cutting costs. Depending on the type of AI application, it can also lead to better accuracy and quality control, as AI by design takes away the element of human error.
Therefore, it’s no surprise that various AI interventions are disrupting even project management.
AI systems cover a wide range of processing, including:
- Machine learning
- Deep learning
- RPA (robotic process automation)
- Natural language processing
- Computer vision
- Digital assistants
While only some aspects of AI may be applicable to project management, there are quite a few ways where it can intersect with existing processes and help make project management tasks much more streamlined.
In fact, there’s a growing market for apps and platforms that can help introduce AI into project management processes. For example, Bitband has a simple project management app that introduces the power of AI into project management functionality. Even well-known communication apps like Slack leverage AI to some extent and there are countless other apps and bots that can be integrated into processes in different ways to take admin pressure off of project managers.
With that in mind, let’s explore ways AI can be leveraged in project management to help run and deliver efficient, cost-effective products.
Staying Agile Using AI
Many software development projects are ongoing, with development happening continuously. AI can help agile processes by introducing new insights that can help uncover more efficiencies, even in existing operations. This can help improve project outcomes and decrease delivery times.
Increasing Project Efficiency with AI
A great AI innovation is the bot, which is the perfect device for managing repetitive, time-consuming, and soul-sucking administrative work that, while integral to a project’s success, can be a drag on time and resources.
Introducing bots to help with data entry, project schedules, resource allocation, documentation, workflows, invoicing, quality control, and more can save a project manager hours. Moreover, bots are easily replicable, so each project gets faster and more efficient over time as successes increasingly get easier to template.
Chatbots can also help project managers minimize daily tasks like check-ins, phone calls, project status updates, meeting coordination, or reallocating tasks. Instead of a project manager needs to step away from other work to send reminders or follow up, the job can be given to a chatbot.
AI for Analytics
AI is much better at processing complex data than a human, with way less likelihood of error. AI is designed to seek out trends and find patterns that might not be obvious to the naked eye – and it can do so in seconds, not hours or days.
Project managers can use AI to gather and parse datasets quickly while being able to see, at a glance, emerging trends and quickly act on them in a way that hasn’t been possible before. Having data and trends at their fingertips, project managers can avoid delays and avoid issues compounding behind the scenes, which helps keep a project on track from the perspective of both budget and time.
Getting Predictive and Prescriptive with Decision-Making
AI can introduce predictive analytics into the mix. This can help project managers with planning and forecasting to more transparently predict delivery times. Since AI is constantly crunching numbers and can deal with large amounts of data, project managers can aggregate data from past projects to analyze outcomes based on multiple criteria and variables. AI might be able to assist in showing how many new hires are required to hit delivery deadlines, for example, or how a budget might stack up compared to past projects of similar scope. Leveraging history and aggregating data points can help project managers, in essence, predict the future. However, it can also help with pivots or scaling a project up or down, as required.
Using AI to Help Make Informed Decisions
Project managers always want to make the right call. With AI, making the right decision, even on the fly, is easier as every choice is backed by data. AI can help illustrate KPIs and show very quickly what’s working – and what’s not. It’s generally removing the guesswork that can often be a part of project management and giving the project manager a clear set of facts to work off of and react to – and a way to defend their decision-making. Ultimately, when AI is added to the mix, project managers never need to predict outcomes and can stop rolling the dice when making a call.
Examples of AI for Project Management
While we’ve already mentioned Bitband’s project management app as an example of how users can integrate AI into their workflows, it’s not the only option. Others include:
- Project management platforms like ClickUp, Asana, and Wrike, that have AI deeply embedded into their processes.
- Otter.ai that helps teams become more effective and reduces time wasted in meetings
- Google.ai which has an advanced ecosystem of open-source tools that can be built into products or used to help manage processes
- People.ai which can be used for teams that are trying to build a better product while measuring customer satisfaction
- Or leverage AI in tools you are already using by exploring Slack’s Apps and Integrations or Jira’s Atlassian Marketplace where there are numbers of bots and AI-powered project management solutions to choose from
Conclusion
While AI may still be relatively new for project management, it’s not going anywhere anytime soon and will only grow more necessary in the coming years. Project managers need to be ready to introduce AI into their processes. And, while project management with an AI twist is quite useful, project managers must be aware that AI-fueled projects require extensive experimentation as AI learns by doing. AI requires an agile, creative project manager who is open to innovation. That said, the benefits can be overwhelming in many cases as AI can remove many redundancies from traditional project management – and along with that, standard human error. By being patient and introducing AI slowly over time, project managers will likely see their tedious workload slowly disappear so they can focus on more critical tasks.
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