We’ve got a few of these devices in our house and it seems that every few days we find a new way to use them. They play music for us, answer math, vocabulary, geography and history questions for my homeschooled kids and tell us weather conditions in some of the areas we are possibly considering visiting or moving to in other areas of the US. Or they simply tell us tomorrow’s weather. It seems they can do anything.
Devices and tech like Alexa and Google Home are nice examples of how machine learning and voice based artificial intelligence are helping us now and learning immediately from their own mistakes and getting better over time to help us more - and more accurately - in the future. Today, just for fun, I said “Alexa, manage my project.” As you may have suspected, she replied with “Sorry – I'm not sure about that” because she can't do that... yet. But what if she could?
Artificial intelligence is infiltrating many areas of our lives – in good ways – that we probably don't even realize. It won't be long till the tools that we use to manage projects will likely incorporate – to some degree initially and to a greater degree over time – some elements of artificial intelligence and machine learning. Future machine learning capabilities of these software tools will bring new meaning to lessons learned!
Think of the uses...
Status reporting. Artificial intelligence and machine learning could be of huge benefit in this necessary, regular and sometimes time consuming and difficult project management responsibility. In the same tool as – or a tool connected with – the project schedule, the resource plan, the financial accounting database for the company that has the codes for every active project and other things I'm not thinking of right now, an AI assisted solution could be instrumental in bringing forth the best and most accurate project status reporting structure ever and be able to change and scale with the individual project and the portfolio of projects as needed by the organization and even the individual project customers.
Requirements gathering. Surveys have shown that IT organizations pay huge dollars for poor requirements gathering. By integrating AI techniques in the requirements phase can the right AI capable tool can have a great impact on this problem and help realize more complete and well documented requirements. Artificial Intelligence is the intelligence of machine, which provides creativity, solving problems, pattern recognition, classification, learning, induction, deduction, building analogies. and knowledge. It is concerned with the study and creation of computer systems that display some form of intelligence and efforts to apply such knowledge and techniques to the design of methods and computer based capabilities to help us effectively manage the business process in the as-is state and the to-be state and properly extract and document all necessary requirements to get us there to that to-be state post implementation.
Budget analysis and forecasting. One of the hardest things about managing the project is keeping it on track financially. A 10% budget overrun is generally not seen as a failure and can be relatively easy to recover from if you stay on top of the financials on a weekly basis. A 50% overrun is a failure and not something you will likely be able to fix by the end of the project - it's just too big. Think about the possibilities for an AI assisted PM tool that was tied in to the organization's accounting system. Of course, cybersecurity and risk management would be a necessary evil of this, but would you like this sort of assistance with keeping your projects on track financially. An enterprise PPM solution with AI capability could be a project manager's and CFO's best friend.
Resource management and forecasting. Just like a tie in to accounting or any financial data for the project can automate, report and analyze the financial piece of the project... AI can do the same for resource usage – especially as it appears over or underutilization is happening or going to happen in the near future on the project. Think of the payback that can happen by knowing four weeks down the road you will have a resource that is 50% under utilized and is not being used by other projects at that time. It can mean that he can be assigned to other projects more easily and quickly or that you can utilize him differently during that timeframe on the current project. The organization is always striving for 100% utilization and sometimes it's difficult to see beyond each individual project – AI can make that happen more easily across all projects.
Lessons learned. If there is one place that AI could help the most and the fastest it could likely be in the Lessons Learned category. Just like machine learning is an ongoing process, so is Lessons Learned. With connections into all key elements of project management tools in use as well as the systems that feed information into them that have been automated, AI should be able to extract the best and the worst of the project to at least at first prepare for the lessons learned sessions. As learning causes growth and additional built-in functionality, an AI assisted tool should be able to document on it's own many of the issues on the project that evolved over the course of the engagement – probably some that neither party was even aware of.
Risk management and cybersecurity. The domain of risk management lends itself particularly well to cognitive computing capabilities, as typical risk issues often include unlikely and/or ambiguous events. Companies and public sector organizations have progressed in terms of using massive amounts of internal and external data to take a more preventative risk stance. Traditional methods of analysis have become increasingly incapable of handling this data volume. Instead, cognitive capabilities - including data mining, machine learning, and natural language processing - are supplanting traditional analytics and being applied against these massive data sets to help find indicators of known and unknown risks. Just as smartphones, online shopping sites, and music apps learn and adapt based on our preferences, cognitive computing can be used to teach computers to recognize and identify risk.
The use of artificial intelligence to manage risk is particularly helpful when handling and evaluating unstructured data - the kind of information that doesn’t fit neatly into structured rows and columns. The possibilities seem endless for AI assisted solutions in the project management / risk management realm. Too many projects allow too little risk management planning – an AI assisted solution could do a far better and more thorough job in much less time saving tens of thousands of dollars in the process on large tech projects.
Summary / call for input
The bottom line is this … we can get better at how we manage projects. Too many failures – yes... some things are out of our control. But I do believe withs many evolving and expanding tools we have at our disposal combined with logical best practices, we can make some of these project failures a thing of the past. Will AI manage our projects in the future? No. But they likely can and will greatly assist us through features incorporated into the project tools available for us to utilize during project engagements. I think it's going to be fascinating to watch the evolution of these features.
Readers – what's your take on artificial intelligence? Do you think it will be part of the project management landscape in the not to distant future? What about this list – what would you change about it or add to it? What's your vision for AI assisted features in project management over the next 5-10 years? Please share your thoughts and discuss – a few visionaries can contribute generously to the PM landscape by sharing thoughts and ideas on this topic.