Are You Willing and Ready to Embrace AI?


The Digital Transformation Playbook - What You Need to Know and Do
Thinkers50 - London - United Kingdom – June 2023

London School of Economics Business Review (Adapted Version)
London - United Kingdom – July 2023

Ricardo Viana Vargas, Ph.D.

Antonio Nieto-Rodriguez

When it comes to artificial intelligence (AI), project leaders should ask themselves two key questions. First: Are my organization and I willing to adopt AI-inspired tools as part of the ordinary course of doing business, particularly in project management? This question will give you a sense of your organization’s appetite for adopting machine learning (ML)–inspired technology. The second—and, in fact, the more critical question—is: Are my organization and I ready to take this important leap forward? This question will give you a sense of how quickly you can identify and apply AI to projects.

The not-so-happy news is that there are many more organizations willing to apply AI to their projects than organizations ready to do it.

Why do so many organizations lag when it comes to being ready? The first limiting factor is a fundamental misunderstanding of the nature of AI and what it can and cannot do for a business. If you are unsure about what AI can do for your business, you are also likely unaware of what you need to do to lay the foundation for AI adoption.

The other limiting factor is a fundamental miscalculation about how people and culture restrict the organization’s willingness to adopt AI solutions. Even the best and most up-to-date technologies can be defeated by leaders and workforces gripped by the uninformed fears about the impact technology can have on their lives.

The only thing we can all agree on is that willing and ready or not: AI is coming!

AI Significantly Improves Project Outcomes

It is no exaggeration to suggest that project management is at the heart of business operations and transformations. Just about everything you do in pursuit of success involves a project of one sort or another. The truly successful organizations tend to be those that can devise, design, implement, and complete projects with more certainty.

In case you were wondering, not all organizations have a grasp on those competencies. The Standish Group, which for several decades has charted the success of technology projects, estimates that only one-third of all projects around the world are successful in achieving their goals. Less than one-half of those projects produce high-value returns.

There are a variety of reasons for this, but one thing is clear: the introduction of AI has the potential to massively improve this woeful record of success. If—and it’s a big if— organizations are both willing and ready to embrace AI and allow it to come to fruition.
Gartner research suggests that by 2030, 80% of basic project management tasks will be run by AI and powered by big data, ML, and natural language processing.

Additionally, new AI innovations are arriving on what seems like an almost daily basis. For example, the business world has only just familiarized itself with the possible benefits of ChatGPT, an AI-inspired chatbot that powers things such as the new Bing search engine. The first version of ChatGPT was released in November 2022 and by March 2023, its creators had already released GPT-4, a fourth-generation version capable of accepting text and image inputs. The incredibly fast pace of change in AI applications puts a lot of pressure on businesses to keep up.

However, not all organizations have the capacity to use AI to improve their business operations and project management. This lack of readiness can be defined in a number of ways, but at the heart of this failure is the inability to find and harness the power of data.

Data is the Heartbeat of AI Readiness

All AI adoption processes begin with data—lots and lots of data, properly consolidated and organized. AI is only as good as the data you have at your disposal, and if that data does not exist, or is poorly stored and haphazardly organized, then you’re going to have trouble migrating from the community of the willing to the community of the ready.

In our research, we found that roughly 80% of the time preparing an ML algorithm is devoted to data gathering and cleaning. That is where we take raw and unstructured data and transform it into structured data that can be used to train an ML model. Once that has been done, the possibilities are nearly endless.

Our own research has shown that, once employed, AI can help organizations select and prioritize the projects they should undertake, identifying launch-ready projects sooner and removing human biases in decision-making.

AI can also help provide faster project scoping, planning, and reporting. It can also help create and implement sophisticated advanced testing systems and software that were once only available to the richest companies engaged in the largest and most costly projects.

Again, however, these dividends are only available if an organization is truly ready to accept and deploy the technology. Currently, we can easily see that there is a broad spectrum of readiness among business organizations—from “all-systems go” to “don’t know where to start” orientations.

The AI Readiness Spectrum: A Checklist for Leaders

How can you tell how ready your organization is? The following questions do not touch on all the concerns, but they do capture major issues that must be resolved before you will be truly ready to embrace AI. Be frank in answering each question and give your organization a score, ranging from one (least ready) to five (most ready). If your organization’s score falls below 24 (an average score of three on each question), then you have some work to do to build readiness:

  1. Do you have the people and patience to build an accurate inventory of all current and past projects, including the latest status updates? This is essential information that will help you determine the scope of an AI implementation project.
  2. Do you have the resources to gather, clean, and structure your organization’s data? Many organizations have data on all aspects of business operations, yet it is hidden away in physical file cabinets on paper spreadsheets or stored digitally in different IT platforms. You need all the data collated and organized on a single platform so that you can get a complete picture of your organization’s potential for project management success.
  3. How ready is your organization and its people to abandon old management habits, such as monthly progress reports, that will be rendered redundant by AI? AI possesses great transformational potential, but only if the technology is used the way it was intended to be used. Asking ML models to pump out monthly progress reports in the same format done before AI arrived is a poor use of the technology.
  4. Are you prepared to invest in training staff on how to use the new technology? It will prove very difficult to fire all existing staff and hire all new staff with more familiarity with AI processes. The best organizations are those that look to up/reskill employees on how to get the full value from ML models.
  5. Are your senior leaders prepared to hand over the reins on the high-stakes decision to implement AI applications? There is very little room for naysayers when it comes to implementing AI. Steps must be taken to educate senior leaders on the potential and limitations of AI solutions so they will be confident when it comes time to lean on the technology to make certain decisions.
  6. Does your organization have a tolerance for mistakes and setbacks to allow time for the organization and technology to grow together? Some organizations simply don’t tolerate failure in any form. Those organizations are destined to be disappointed with AI solutions, particularly if they don’t work exactly as promised right out of the box. AI is not a plug-and-play technology platform; it requires organizations to evolve and learn how to use them to full advantage.
  7. Does your organization have an executive sponsor with both the expertise and credibility to lead an AI transformation? This cannot be a case of the blind leading the blind. Your employees want to know that the executive sponsor has intimate familiarity with the technology and can explain precisely what it can and can’t do.
  8. Does your organization have the patience for a transformation that can take years to fully accomplish? Leaders who suffer from a lack of delayed gratification will likely not have the patience to see an AI transformation reach fruition. Patience is not only a virtue in this scenario, it is the lifeblood of AI transformation.

AI and ML models are truly the future of project management. Of this, there is no doubt. The uncertainty, then, is not about whether your organization should embrace AI; it’s about whether your organization is willing and ready. These questions can only be answered through a process of unblinking self-assessment. It is time to go forth and ask your organization some tough questions. The payoff could be the ability to be among those leaders adopting AI rather than being left among the laggards.

Read the published article at LSE Business Review

Transformation , Project Challenges , Project Management , futureofprojectmanager , AI
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