Tag Archive for: Artificial Intelligence

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Can AI replace project managers? We asked ChatGPT.

Most of you by now, if you weren’t already aware of it, will have noticed in the media the buzz around ChatGPT, an AI chatbot launched in November 2022 by OpenAI. With a small amount of existential trepidation we went straight to the question that matters (to us!) most: “Can AI replace project managers?”.

While the writing style is a little formulaic, it provided an interesting breakdown of where AI could and could not currently assist in the delivery of projects, highlighting the key skills that project managers bring:

“Can AI replace project Managers?” – response generated by ChatGPT

Artificial Intelligence (AI) has the potential to revolutionize many industries, including project management. However, it is unlikely that AI can completely replace project managers in the near future. While AI can assist project managers in certain tasks such as scheduling, resource allocation, and risk management, project management involves a lot of human interaction, decision making, and problem solving, which are still difficult for AI to replicate. Additionally, project managers also play important roles in communication, motivation, and leadership, which are not easily replicated by AI.

One of the main responsibilities of project managers is scheduling, which involves creating a plan for the project, setting deadlines, and ensuring that all tasks are completed on time. AI can assist in scheduling tasks by analyzing data, identifying patterns, and making predictions about project timelines. However, AI systems lack the ability to consider all the nuances and variables that a human project manager can take into account while creating a schedule.

Another important responsibility of project managers is resource allocation, which involves determining which resources (e.g. personnel, equipment, etc.) are needed for the project, and ensuring that they are available when needed. AI can assist project managers in resource allocation by analyzing data and identifying patterns that can help predict resource usage. However, AI systems lack the ability to make judgement calls and take into account the human aspect of resource allocation, such as personal abilities and preferences.

Risk management is another important responsibility of project managers. They need to identify potential risks that could impact the project and take steps to mitigate or avoid them. AI can assist project managers in risk management by analyzing data, identifying patterns, and making predictions about potential risks. However, AI systems lack the ability to anticipate and mitigate risks that are not based on past data.

Project management involves a lot of human interaction, decision making, and problem solving, which are still difficult for AI to replicate. Project managers need to be able to communicate effectively with team members, stakeholders, and clients, adapt their communication style to different audiences and be able to explain complex technical concepts in simple terms. AI is not yet advanced enough to replicate this level of communication.

Motivation is another important aspect of project management. Project managers need to be able to motivate team members to work towards a common goal, and to overcome obstacles. They need to be able to create a positive and productive work environment. AI is not yet advanced enough to replicate this level of motivation.

Leadership is also an important aspect of project management. Project managers need to be able to lead teams and make important decisions. They need to be able to set a vision for the project and inspire others to work towards it. AI is not yet advanced enough to replicate this level of leadership.

In summary, while AI can assist project managers in certain tasks, it is unlikely to completely replace them in the near future. Project management involves a lot of human interaction, decision making and problem solving, which are still difficult for AI to replicate. Additionally, project managers also play important roles in communication, motivation, and leadership, which are not easily replicated by AI.

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AI for Projecting clients

A year ago we published an article introducing DELTA AI, Projecting’s sister company focused on AI. Since then, the DELTA team have been busy talking to potential clients about AI. In Projecting Group we like to use initial client meetings to understand their needs (as we discussed in a recent DELTA AI article). However, clients often want us to lead with relevant use cases, as a good way to spark the conversation. There are many interesting use cases in the market, but most consultancies don’t go beyond the well-known offerings of the big well-funded players. One of DELTA AI’s strengths is that we have taken the time to investigate and understand the offerings of lesser known / earlier stage companies. This is where much of the innovation is taking place, as 89% of the AI ecosystem in the U.K. consists of startups with 50 or fewer employees (according to this Forbes article).

We see 3 main ways AI can help companies:

What is AI?

(See also this video from an event earlier in the year. It is in Spanish, but if you turn on the automatic English subtitles you will see a good example of the power of AI).

Over the last year, we’ve met many Projecting current or potential clients keen to talk about AI. This is already resulting in projects with an AI component.

A good example of this is the work we are doing with a company in the Wealth industry. The client asked Projecting to help them transform their Operating Model. In the first phase, working with a DELTA AI expert, we identified 3 main ways to apply AI to obtain quick wins. For the first opportunity, we are currently reviewing off-the-shelf tools. For the other two opportunities, we are developing business cases for building customised bots.

The DELTA AI team continue to focus on expanding knowledge and expertise in AI. We hold regular sessions across the teams to ensure the Projecting team are aware of the latest use cases identified. So, if you are interested in AI, feel free to contact anyone in the DELTA AI or Projecting teams. We’re always happy to have a chat.

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Introducing DELTA AI

delta-ai.com

We attend a number of conferences and events and meet a lot of Fintech startups, working at the forefront of Artificial Intelligence, Blockchain and other technologies. This is fun and fulfilling at a personal development level but also helps us be able to think outside the box in our daily conversations with our clients. Often their challenges or objectives can be addressed relatively quickly and inexpensively using Artificial Intelligence solutions, such as Robotic Process Automation, predictive modelling based on Machine Learning or something as simple as a chatbot. This usually comes as a surprise to them as their experience of AI is as a hyperbole-filled topic oversold and under-delivered in the market to date. Most of our clients haven’t got the time to separate fact from fiction so we do a lot of educating in simple language about AI and what is and what isn’t achievable.

We are at an exceptional point in the market when it comes to the possibilities of AI. Most organisations haven’t even begun to scratch the surface and there are plenty of low-hanging fruits that can be quickly and easily captured. To illustrate this, here are a few very simple yet powerful use cases that we have discussed in recent months with clients:

  • Churn predictor: using Machine Learning over existing internal data to predict which customers are most likely to leave and focus your retention efforts more accurately. If you can reduce your churn levels and maintain your underlying customer acquisition, your growth automatically increases! This doesn’t need setting up a data lake or buying social media feeds, you can generally get good results with internal data
  • Onboarding process automation: using a Robotic Process Automation tool, you can (very quickly) automate the (usually very manual) process of running any customer checks, setting up details on different systems etc. Over time you can apply Machine Learning to this so that any exceptions are learnt from and your manual involvement keeps going down
  • Sales team augmentation: there are multiple tools already in the market that can be implemented to augment your sales team’s capabilities. From virtual PAs that allow your team to hand off scheduling and meeting booking to a machine, to intelligent insight preparation based on your internal CRM and external news feeds that can warn your sales team when they should be contacting a customer or what products they are likely to be interested in
  • Agent Help desk: if you rely on an external network of agents to bring you business and be the face of your brand, you need to make sure they understand your products, tools and processes. Often queries are very simple and easy to deal with but require a human to interact with the agent, introducing delay and increasing the likelihood of confusion. A simple chatbot interface can help address the majority of queries quickly and inexpensively allowing the human team to focus on the more complex questions

To address these types of challenges better, we have set up DELTA AI as part of the Projecting Group. At DELTA AI we are already working with various clients on implementing AI solutions. DELTA AI doesn’t build software but bridges the knowledge, cultural and language gaps between our clients and startups to deliver practical solutions, simply and inexpensively. In the coming months we will be posting a series of articles detailing what types of solutions are feasible in each part of the financial services sector. In the meantime, for more information please visit the DELTA AI website (delta-ai.com) or speak to any of the Projecting team.

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