Artificial Intelligence (AI) and Project Management are being discussed together for a while now.
Rather seriously! There is anxiety and excitement in almost equal measures among professionals across the globe.
What makes Project Management so relevant for Artificial Intelligence (AI)?
The answer is straight forward and lies in the very definition of AI and Machine Learning (ML). Let us take a look.
As Wikipedia states:
Artificial Intelligence or AI sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans. Colloquially, the term “artificial intelligence” is often used to describe machines (or computers) that mimic “cognitive” functions that humans associate with the human mind, such as “learning” and “problem solving”.
In simpler terms, AI enables machines to learn, think and act like humans. AI uses data, servers and algorithms to train machines for specific actions such as recognizing objects, reasoning, problem solving, planning, and perception.
Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use in order to perform a specific task effectively without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence.
After careful review of both their definitions, one can safely state that AI and ML help provide deep insights from a huge data source built over time which is often difficult to track by us.
If you take a further closer look, ML enables identifying patterns and structures within the data and predict outcomes of specific activities.
Do note that the data is nothing else but “human actions and inputs recorded by various systems during the course of a specific activity or a project”.
Coming back to our original question, a project is an endeavour with tons of tasks and activities, some repetitive and manual to quite some extent.
Plus, projects include a lot of guess work and gut feeling items w.r.t time and cost estimates, risks and anticipated outcomes.
The fate of our projects and business cannot be just left on a project manager’s anticipation or gut.
Also the lessons learnt from projects are often not recorded or referenced properly for future projects which creates quite a knowledge gap in the organization over time.
Hence, AI would come in real handy here.
So at a high level AI can help turn project management into intelligent project management with:
- Predictive Analytics – risks and uncertainty management
- Big Data Analytics – performance improvement & management
- Insightful Automation – removal of repetitive tasks
- Cost Reduction – accurate project estimation
Let us now explore how each of the above benefits would be distinctly realized for project management.
Referring to lessons learnt from past projects is of utmost importance in running strategic initiatives project management office (PMO) successfully.
A project has multiple moving parts that one cannot control all the time. And a very many fall out of the circle of influence of the organization itself at times.
Hence, being supported by accurate insights on a probability of certain risks goes a long way in preparing, preventing and mitigating them.
To me AI has the capability to enable uncertainty management in certain terms!
With AI’s ability to synthesize large past datasets across multiple system of records (SoRs) from various projects, you can obtain definitive insights into what will work, what won’t and also forecast relevant project outcomes.
Imagine a system presenting you a report every morning stating how many issues you will encounter today e.g. infrastructure management, storage devices or other hardware based on historical issue logs, requests etc.
Wouldn’t you be well prepared to manage them for optimum customer satisfaction? Or fix the product glitch to prevent the other 1000 issues waiting to be reported?
The upside: you can do better resource management, allocate the right budget or funds, proactively fix your processes, amend project plans to save millions of dollars.
How wonderful that would be for a project manager?
Big Data Analytics
Task planning, assignment, resource allocation and meeting deadlines are a daily battle for project managers!
And add to it, numerous reporting requests from various stakeholders throughout the day and week. Suddenly a PM becomes more of a reporting analyst.
Humongous waste of precious efforts and too manual intensive!
AI enabled project management turns your basic project reporting to highly actionable insights. They are no more mere numbers and data.
Gartner says – by 2030, 80 percent of the tasks involved in project management will be eliminated. Things like data collection, tracking and reporting will be taken over by AI.
Effective resource allocation and planning is the most challenging activity for us all.
With big data analytics, you have ready information on what is available, how much more is needed and most importantly when!
Resource conflicts are handled pre-emptively! In other words, running your programs and managing the entire project portfolio becomes a lot easier and profitable.
Most importantly, you are in the driver’s seat with absolute control over your project and their outcomes. i.e. higher project success rates!
Why would you not adopt AI?
Our projects are filled with multiple simple yet time consuming repetitive tasks. Often non-billable!
Continuous monitoring of your actual vs planned is an uphill task. Be it costs, resources, time or progress. You have to constantly track them to ensure your project is making the right progress and will be completed per agreed schedule.
A new report issued by the McKinsey Global Institute in late 2017 suggests that as many as 375 million workers globally, or approximately 14 percent of the global workforce, will be impacted by automation and may need to evolve their skill sets to adapt to the impact of AI.
The issue here is, the estimation is dependent on the expertise of the project manager. There are lot of assumptions in effect and neither are these backed with reliable numbers.
The result – inflated costs and project duration. Neither augurs well for you, the project or the client.
This changes drastically with the power combo of AI and ML.
The combined ability to provide near to accurate productivity rates, time estimates based on analysis of past project performance optimizes your overall project management posture.
Moreover, automation reduces time spent on repetitive manual tasks and helps save dollars with possible reduction in project duration.
The upside – more time for complex and billable activities, higher ROI, optimal resource utilization and robust & scalable task management across the organization.
The points we have discussed so far have one common benefit – Cost reduction/ Higher ROI.
And a MIT Sloan survey states that 63% of people cited cost reduction as the main objective for AI adoption.
So, how can we achieve it?
- Better estimations on time and efforts helps save money.
- Automation of repetitive tasks also helps reduce human efforts which translates into cost savings.
- In-depth predictive analysis helps in effective risk prevention and mitigation thereby enabling lower project contingency funds and higher profits.
- Insights on productivity rates can help optimize them over time thereby project teams achieving more with less.
- Time saved from routine tasks, can be redeployed for more complex and core activities leading to increased business and revenue.
There is visible trend of AI adoption in project management.
Very many providers of project management software, task management and collaboration tools are focused on developing chat bots and adding AI enabled functionalities to their tools.
More so, as it is anticipated that AI will enable overall planning, designing and optimizing complex architecture along with significant contribution to the customer support and QA streams.
It will be easier for companies to understand their resources, enrich their talent pool and optimize productivity rates.
Crucial data analysis activities will see a significant reduction in turn-around time and actionable insights would be available in real-time with a few clicks.
Overall, there will be both horizontal and vertical impact on the current roles of the workforce across organizations. Be it project managers, HR, IT managers, Data Analysts, Data Scientists, Solution Architects, Customer Success Managers, Developers, and Quality Analysts etc.
The impact need not be negative. In fact, it would entail a lot of upskilling and reskilling of resources to adapt, adopt and be adept in the use of AI.
Maybe very soon there will be quite a few Tony Starks with their own Jarvis’ after all!
But that’s a story for another day