Imagine the brave new world of Project Management equipped with the power of Artificial Intelligence, where Project Managers do not have to spend endless hours trying to make sense of data (often incomplete data) spread across disparate and disjointed systems, make project plans based on guesstimates, tenaciously track project status by chasing individuals for updates. Instead they can leverage the powerful insights of AI tools that can analyze , improvise by self-learning heaps of project data to predict and plan schedules, estimates/timelines, budgets, resource allocation etc allowing Project Managers to spend their time focusing on other important things like making sure that the team is well equipped to deliver the project on time, the dependencies are identified and communicated, the risks are understood and mitigation plans are ready, negotiate with cross functional teams for smoother execution of the project etc etc. With the rapid development in the field of AI , especially in machine learning and machines ability to deep learn , there is a huge potential that could change the face of project management altogether and make it possible for machines to handle routine project related work to aid the PMO.
PMOs Current Challenge
Today most Project Managers deal with the frustration of planning and tracking projects with incomplete data which depends on human input and people who are responsible for entering the information have no real incentive of doing it. How often someone feels incentivized to update her task status regularly or update the estimates based on new findings, yet doing so is a very important part in order to understand the current state and predict the schedule of the project.
While AI brings in a lot of possibilities to the table for project management, in near future there are two key areas that could benefit tremendously from AI driven evangelizing- Estimates and Tracking.
The data driven estimates
The ability to estimate right is the primary building block of a good project plan, it brings in predictability and visibility to the project. As humans we are not so good with estimates, we either underestimate or overestimate. Most of the time our estimates are only partially based on facts; intuition, emotional and psychological factors play a significant role in this as well.That’s why many a time we call it guesstimate.
There can be many different factors that influence the answer to a simple question “How long do you think this task/work will take to finish?” For some the answer could be 5 days (It took me 10 days last time for something similar but if I say 10 days maybe I won’t get the project . Let me get the project first, I can negotiate the timeline later ) or for some it could be 15 days ( Well it took me 10 days last time , but I want to make sure I keep some buffer ). These kinds of guesstimates might mislead the project plan and schedule.
Machine learning algorithms can tremendously help in such situations by making estimation suggestion based on the prior history and the context. And feeding the algorithms with good quality and well-organized data sets would enable them to provide much accurate results than human intuition.
Day to Day tracking and Status:
While the regular status update is a very important part in order to understand the health of a project, however updating status by individuals are not a very incentivized process and Project Managers spend more than necessary time chasing people to get status updates. AI driven self-learning bots can help tremendously in this space. Many a time people forget to update status as they have tons of other things on their plate.Bots can interact with people on a regular basis and provide them easier ways to update the status quickly and take back that information to update the project management system. This can drastically cut down the status only meetings, free up more time for people to do more fruitful things. Many a time people find it less pressurizing to deal with bots than a human asking for status. These bots could also provide useful insights to individuals in terms of prioritizing their workload and efficiently manage their time along with options of providing a feedback loop to improvise day to day tasks which can be a strong incentive for people to enter the right input.
Will algorithms replace the human Project Manager
If AI takes over most of the routine work which is considered core PM responsibilities what will it mean for the future of Project Managers? Can machines automate project management to eliminate the need of human Project Managers altogether? It is a valid question and not only limited to the field of project management. In recent years with more and more focus in AI driven tools and applications, there is a growing anxiety about jobless future in every field starting from manual labor intensive fields to highly skilled science and medical domains.There is a huge potential in using AI in project management and it is worth exploring. However, would it be a threat to the job of a Project Manager? I strongly doubt that. According to the experts, the vulnerability of a job to AI and automation depends on how much of it is routine and can be automated.And it is obvious that most of Project manager’s job is far from routine.
Project Manager’s role is not about creating reports, tracking statuses. Her primary role is to get things done and take the project to a successful completion by making sure the team has the right capabilities and environment to do so, remove impediments and obstacles that can block the progress of the team. This requires tremendous understanding of team dynamics and culture, negotiation skills, conflict resolution capabilities to name a few. A successful Project Manager is resourceful, tenacious and ready to walk the extra mile to make things happen for her team. These are the skills that no amount of AI automation can replace, at least not in near future and when(if) it does all kinds of jobs will be at risk. Using machine learning and deep learning algorithms to gain valuable insights would tremendously help PMs to be more efficient and productive.This is the genie every Project Manager secretly prayed for. Project management has always been a role that heavily relies on data to predict, plan and execute.It only makes sense to use latest and greatest in the field of data analysis and use it for advantage.
Throughout the history, there have been repeated predictions of machines taking over jobs. During the industrial revolution, there were huge uproars among textile workers who feared that machines will replace them. However, as more and more weaving process was automated workers shifted their focus to do things that machines couldn’t do like operating, maintaining the machines etc. The automation of textile industry led to more production which in turn reduced the prices, resulting in rising consumption and increase in demand.This fueled the loop by the increase in production and creating more jobs.
Similar fear was predicted as computers made their debut.But today we all know how that story goes. One of the classic examples cited in an article in The Economist, the introduction of ATMs was expected to threaten the job of the bank tellers. However in contrast, with ATMs automating some of the routine tasks, the running cost for banks were significantly reduced, encouraging banks to open more and more branches leading to increased number of employments.
History is full of numerous examples of how automation has created more jobs than ever. However, it is also true that with more and more automation the type of skills required for the job has changed. With AI empowering different fields, none of the jobs will remain same, there will always be a need to upgrade and adapt to new skills.
Sharpening the skills for future
In future, I see the Project Manager encompassing the bigger role of data curator and data architect for any project related data among other things.With advent of collaborative project management tools which can integrate and pull data from different mediums of communication like wiki, chat applications, emails, source control systems etc, it is extremely important to make sure the quality of data is good and data integrity is maintained throughout so that AI algorithms can make better sense of them.Future Project Managers would definitely need to get their hands dirty to make sure the data is clean.
There is an enormous potential in harnessing the power of AI for project management. Many companies are already experimenting with it. This is definitely a space to look out for in near future and gear up to take advantage of it.
