Artificial Intelligence – Not New, But Better!
When ChatGPT became publicly accessible in November 2022, artificial intelligence (AI) gained attention from a wider audience than simply “techies” and long-time AI enthusiasts. Artificial intelligence is not really new, after all. The 1900s saw the beginning of the development of AI [1].
A computer software known as a “chatbot,” ChatGPT was created by the American AI research center OpenAI with the intention of simulating communication with human users. With the right guidance, it can write poetry, create computer code, schedule trips, translate across languages, and perform a host of other tasks. Microsoft debuted a comparable chatbot on its Bing internet search engine two months after ChatGPT made its debut. It also unveiled Copilot, its “everyday AI companion.” Google released Bard in March 2023, whereas ERNIE Bot was unveiled by Baidu, a global Chinese technology business that specializes in Internet-related services.
These chatbot apps make it simple to argue that artificial intelligence (AI) will eventually permeate every aspect of technology. But as journalist Steve Lohr of The New York Times pointed out sagely [2], history has shown us that significant new technologies take time to become widely used. This is true for everything from steam power to the internet. Using the Internet as an example, he said that there were audacious forecasts made in the 1990s that the web and the Internet would upend the media, retail, and advertising sectors. Though those forecasts came to pass, the real disruption didn’t happen until over ten years later, when the dot-com bubble had crashed. Over that period, costs decreased, technology advanced, and bottlenecks disappeared.
There are currently several reasons why businesses are hesitant to deploy chatbots immediately, including concerns about data security, potential for data leakage, systemic biases, and the accuracy of AI-generated responses that may cause “hallucinations” or be loaded with inaccurate information.
How AI Is “Here” Already For PM?
Based on a historical review of different technologies, McKinsey & Company projected a range of AI-applications adoption durations from 8 to 27 years between the beginning of adoption and its plateau in a recent paper (June 2023). This range takes into consideration the several variables, such as regulations, investment levels, and managerial decision-making inside businesses, that may have an impact on the rate of adoption [3]. Experts in the field of project management (PM), which is the focus of our investigation, estimate that by 2030, artificial intelligence (AI) will replace traditional project management tasks including data collecting, tracking, and reporting, eliminating 80% of the labor performed by today’s PM discipline [4].
According to a fascinating analysis by PwC [5], AI-enabled project management tools help and improve decision-making processes more, and they may be essential in the near future for attaining successful project management in the following five critical areas:
Business Knowledge. For instance, the system can eliminate “white noise” and unnecessary information by finding patterns and trends in the data. This allows management to concentrate only on the most crucial and pertinent facts in order to produce strategies and insights that can be put into practice.
Control of Risks. Proactive risk management is necessary for effectiveness. AI makes predictions about risk reactions, probabilities, and impacts that are more accurate than those made by conventional software solutions. Based on past performance, AI can recommend corrective action and monitor development continuously to alert the project manager to potential risks.
Optimization of Human Capital. AI is able to determine the optimal use of resources by matching available workers with various tasks according to their availability and skill set. It is simple to consider aspects that contributed to past achievement.
Take-Action Person. For instance, businesses in the construction sector are integrating AI with drone technology by deploying drones to monitor and record data from construction sites, and then employing deep learning to accurately identify personnel, equipment, and supplies. Project management solutions with AI capabilities can then recognize risks and concerns that call for immediate action, reporting progress and offering advice to the project manager while taking direct action when necessary.
Active Support. A frequently performed function by the PMO is providing status and progress reports to various stakeholders, including upper management. By handling routine and administrative work for project managers, artificial intelligence can complement their abilities.
Two things need to be noted when applying AI to project management:
human elements. Experts are certain that artificial intelligence (AI) will fundamentally alter project delivery and the direction that project management takes. But it’s crucial to keep in mind that AI is not capable of being a human. This indicates that if project managers concentrate on the fundamental competencies of project management—leadership, empathy, emotional intelligence, and negotiation—they will likewise be important in the era of artificial intelligence [6]. Owing to all of these uniquely human qualities, project managers are able to lead teams, inspire employees, and maintain their focus on completing tasks successfully[7].
Application and Execution Work. According to the Harvard Business Review[8], Nieto-Rodriguez and Viana Vargas emphasize that a significant amount of project-related data will be needed for AI systems to be trained to manage projects. Data collection and cleaning, which converts unstructured and raw data into structured data, takes up around 80% of the time required to get an algorithm ready for usage. Additionally, these professionals offer a series of inquiries that can be used to evaluate the choice to use AI. These inquiries include the following:
Are you prepared to invest the necessary time to create a precise list of all the projects you have, together with the most recent progress report?
Can you dedicate a few months and a number of resources to compile, organize, and sanitize your project’s data?
Are you willing to spend money educating the members of your project management community about this new technology?
Are you prepared to accept that this technology will make errors on its way to improving performance for your company?
Are top executives prepared to wait a few months or perhaps a year to witness the advantages of automation?
Applications Of Generative AI In PM (A Non-Exhaustive Summary)
The usual daily workload of a project manager is extremely busy, as people who work in the field are aware. This includes conducting or attending meetings, making decisions, reading, responding to, and categorizing emails, as well as interacting with team members. Having a trustworthy assistant can come in extremely handy.
Forbes[9] has noted that AI systems are capable of managing follow-ups, reminders, and scheduling. By assisting in making sure that nothing is missed, these technologies can help humans save time on their numerous tasks. To provide a more effective workflow, these solutions interact with widely used project management tools like JIRA and communication platforms like Slack.
For instance, PMOtto software[10] is a virtual project assistant that can use past data to update project status and KPIs and provide advice. For example, a user can instruct PMOtto to “Book John’s painting of the wall for next week, and give him full time for the task.” “Based on previous similar tasks allocated to John, it seems that he will need two weeks to complete the work and not one week as you requested,” the assistant may respond. Should I make any adjustments? [8].
Three software programs are noteworthy in relation to the meetings: OtterPilot, adam.ai, and Fireflies.ai. based on their websites:
An AI meeting assistant called OtterPilot can attend meetings, record audio, take notes, capture slides, create summaries, and respond to team inquiries [11].
Adam.ai is an intelligent, all-in-one platform for managing meetings that facilitates knowledge capture, sharing, and management before, during, and after meetings. It also turns content into valuable assets and helps businesses achieve their goals [12].
Across a number of video-conferencing apps, Fireflies.ai records audio and video and produces transcripts in a matter of minutes [13]. This enables the project manager to spend more time looking up, concentrating on the vocalics, body language, and other non-verbal cues of meeting stakeholders—something that is still best done by a human—as noted in Great Meetings Build Great Teams [14].
We may envision a platform similar to the one in the following image being run by project managers in the near future with the aid of AI assistant software. This could provide the project manager with helpful recommendations and enable the information on the platform to be updated.
Information becomes fragmented when a project manager employs many, non-integrated software programs. The perfect aide aids in the integration and synthesis of a project’s most crucial metrics or indications. When a status meeting regarding the project begins, the platform ought to be available, with all fields updated and discussed. In this instance, too, the customary meeting memo that is often given to the participants will be superseded by an immediate update that is visible to all stakeholders on a shared platform.
As is now abundantly clear, artificial intelligence will be crucial to project management in the future. It is crucial to take the initial step now (by utilizing the AI Assistants) and be ready for the subsequent actions in order to reap the rewards.
In Summary
The aforementioned factors lead us to the conclusion that while AI can support PM (with some effort), it cannot take the role of project managers. AI is a useful tool, but it must be employed as an assistant if you want to see a noticeable impact right away. This is project managers’ first move into AI.
By understanding how to “engineer” cues and “converse” with Generative AI systems—that is, by being aware of these systems’ limitations and capabilities—project managers can become more adept at deploying AI.