“AI is neither friend nor foe by default. It can be a powerful catalyst that reflects the intentions and actions of the leaders and employees who deploy it.”

Why AI feels different

When I reflect on Artificial Intelligence (AI), I often imagine technology so powerful that it can free employees from repetitive tasks, reveal organisational insights that no employee could discover, and fundamentally change how an organisation operates. From what I have read, seen and helped deploy, this is AI as of 2025 and no longer a figment of my imagination.

When I was asked to write this article, I instantly thought that I could share all the research I conducted during my postgraduate and doctoral research on transformation and organisational change, and highlight how, over the past two years, the number of articles on AI has nearly doubled (from 2023 to 2025). However, I thought it might be more interesting to focus on my experiences to date and where I believe AI might go in the future. I also wanted to highlight my own personal view, which some of you may disagree with, but I hope it will provide food for thought!

When speaking with one of my friends, we discussed the power of emotions, nuance words to convey a point of view and how interesting it can make reading a piece of work with a particular style, we also discussed the power of automation and how AI can generate ideas and content so quickly and provide structure to an article so easily but perhaps the final output can be a little clinical or lacks purpose even though it is technically correct.

A recent article in the Harvard Business Review, by Niederhoffer, et al., (2025, p. 1) coined the term “Workslop” and highlighted that it is where employees use “AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task”. This solidified my approach to writing this article, to ensure I focused not only on the amazing things that AI can provide but also the negatives that could come from it, if employees use it without consideration.

Before we dive into AI and try to answer the question, Is AI friend or foe?, it is worth giving you a brief overview of my background. With over two decades in financial services, technology, supply chain, airline, consulting, and regulated industries, I have delivered digital transformations, overseen enterprise portfolios, built PMO functions, led development and test automation teams, managed change management and business analysis teams, and guided teams through complex organisational change. I have seen many new innovations arrive with much fanfare, often termed “bright shiny objects”.

I see some similarities between the introduction of Agile methods and the excitement around AI. The rise of Agile changed processes as we know them, but I believe Agile is a toolkit and philosophy that helps us to deliver the required business outcome in a better way. Many people view AI as being exactly this: it is a tool to help deliver fundamental business change. However, I do believe that AI’s impact will be far more fundamental and lasting. I believe that achieving meaningful AI impact requires a shared understanding (e.g., of goals) and transparency between organisations and their employees of good uses of AI. This shared wisdom will empower us change professionals, but we must upskill ourselves to recognise things like “AI Workslop”, use AI to help tidy and structure good work that employees create and deliver value within organisations, just as we have been doing for many years.

There are so many questions about AI that I, and I suspect others, would like to have answered, including 1. who will benefit more from AI, organisations or employees? 2. How should leaders plan for AI’s transformative power? And 3. what do I think the future might hold in the face of AI? Throughout this article, I’ll try to provide my view by answering these questions and offering some learned experience about integrating AI without leaving people behind.

Please note, these are my views and expressions and not the views of any organisation that I may be or have interacted with.

1. Who will benefit more from AI, is it organisations or employees?

1.1. From research to reality, my first encounters with AI

“What seemed ambitious three years ago is now reality.”

Much of my research to date started with organisations using AI and Machine Learning to focus on customer support, and in particular, Chatbots. Systems that would take a query and search for a response. In addition, employees and students were also using AI to write part of their submissions or provide information to specific questions. At the start, I remember that the hallucination rate was quite high, with AI answering questions incorrectly. But during my doctoral research, I tracked AI related academic publications and observed (by my calculations) a nearly 2000% increase in the number of AI articles in just four years. This shows how quickly the AI world was moving.

However, rather than just focusing solely on research, I want to share my direct experiences and observations as well. I vividly remember my first discussion about introducing AI into any organisation’s ecosystem. The AI we were considering was far less sophisticated than today’s agentic AI opportunities. Looking back, what seemed ambitious then is now a reality. Since that first conversation, I have witnessed what I believe is the fastest growing and most rapidly evolving technology in history. I have seen organisations make claims of revolutionised customer journeys and saving millions through AI, machine learning, and automation. I have also seen leaders use AI as a catalyst to revisit strategies (in some cases, tear up previous strategies and create new ones), modernise systems, and transform operating models. Some organisations replaced legacy workflow layers with AI agents, while others are experimenting with ‘super agents’ that can trigger multiple supporting AI agents.

However, research has highlighted that long term benefits were not measurable, and many are unsubstantiated claims (Challapally, Pease, Raskar, & Chari, 2025). This MIT research highlighted that “95%” of researched organisations hadn’t seen a measurable return on investment. I wouldn’t take this as a definitive study, as I have seen many organisations measure and achieve benefits.

In a recent technology transformation, I witnessed AI being introduced under the banner of automation to free project teams from routine tasks. However, the initial reaction amongst employees was mixed. Some feared job losses, while others were cautiously optimistic. A few months later, when I revisited the teams, most felt relieved. Freed from admin heavy work, they were spending more time on strategic or creative tasks they enjoyed. Yet this was not the case for all employees. One employee reflected that creating status reports and action logs had been a calming, almost meditative part of their day. For them, the loss of that routine was unsettling. This reminded me that even well-intentioned changes have complex emotional effects.

1.2. Organisational gains and employee impacts

Over the past few years, I have watched automation and/or machine learning (under the banner of AI-driven analytics) detect fraud patterns faster and more accurately than any human team. In supply chain operations, predictive AI has reduced waste and improved delivery schedules. These advances bring clear organisational benefits, but they also highlight a growing tension and a key question: Will AI’s benefits flow mainly to organisations (in increased profits and reduced costs), or will employees share in these benefits?

My experience, so far, shows that the answer depends on the leadership choices. When employees are engaged early, supported through upskilling, and given a voice in shaping AI use, they become innovators and advocates. However, when they are left out, change-related fear, anxiety, and resistance grow. While conducting a recent study into resistance, 60% of respondents highlighted that they had an increasing level of anxiety towards AI use and adoption within their organisation (Pullen-Ferreira, 2025). Organisations that succeed understand that AI must augment, not simply replace, human capability.

2. How should leaders plan for AI’s transformative power?

Many people may think of AI as a reactive platform, where you ask it a question or provide a well thought out prompt and expect a specific answer. AI should be built into strategy from the start; it cannot be an afterthought or side project. I have used various automated platforms, built on machine learning, to be a PROACTIVE force to highlight when things were off track. Connecting projects to measurable outcomes, such as customer retention or revenue growth, can secure executive support and guide investment decisions; however, it is essential to know if these investments are providing the desired benefits and if they are off track, then they should be stopped. I believe that AI can become that early warning system that allows you to check if something is wrong before a risk turns into an issue.

I have also found that piloting before scaling is critical. By starting small and learning quickly, I have protected investment while building confidence. On a recent project, where I was coaching a team, we ran controlled experiments, gathered insights, and only then expanded across geographies due to the regulatory and regional considerations. Ethical governance has been equally important. In regulated industries, unchecked AI can create significant risk. Therefore, establishing clear guidelines on data privacy, bias mitigation, and transparency are essential for building stakeholder trust.

Finally, reskilling cannot be overlooked. Whether working with analysts or supply chain managers, I have invested in developing data literacy and AI fluency (sometimes just the basics make the biggest difference). This transforms employees from hesitant observers into active contributors, enabling them to fully leverage AI tools.

2.1. The human element, addressing fear and building trust

My doctoral research focused on how people respond emotionally to organisational change. AI is a prime example of change that triggers both excitement and anxiety. I have seen organisations focus on creating AI solutions and not waiting until deployment to communicate with employees. When we engage employees early through workshops and prototype demonstrations, this gives them a sense of ownership and in most cases reduced resistance.

I also make it a priority to acknowledge the emotional side of change. In a recent transformation, we celebrated how automation and machine learning created more time for staff to interact with passengers. This human-centred framing mattered far more to employees than cost savings or operational metrics. Leaders who treat AI as purely a technical implementation, risk alienating the very people who can make the transformation succeed. Trust, transparency and empathy are essential for adoption.

2.2. Avoiding common AI pitfalls

Over the years, I have observed several recurring mistakes in AI, Automation and machine learning adoption.

• Treating AI purely as a technology deployment rather than an organisational change initiative is one of them.
• Poor data quality and AI misuse undermine AI effectiveness, as highlighted by the recent news article about the misuse of AI to create a report in Australia(Tadros & Karp, 2025).
• Skipping governance can create reputational and compliance risks, as highlighted by several organisations having to apologise for AI creating false or derogatory results.
• Neglecting change management and communication can create unnecessary fear and resistance, even when the technology works perfectly.

While most of the above are organisational-focused, from my personal view, there is an employee’s reputational risk at stake if individuals use AI to draft all their work, versus using their creativity. I highlighted the concept of workslop earlier in this article, and if employees use AI without considering the impact, I believe that they will be perceived as less creative, capable, reliable, trustworthy and intelligent, as highlighted in Figure 1 (Niederhoffer, et al., 2025, p. 3).

I have thought a lot about this section, as AI is a quick way to get facts and can be extremely helpful. But there is always a catch to something for free, and in the case of using AI to create presentations, do homework, write articles or draft emails, it can lead to a reduction in our own ability to be creative when developing content. I have seen some people who use AI frequently feel less capable to create future content, which is demoralising when these were some of the most creative people I know. This concern was highlighted in a study by MIT, which highlighted the cognitive loss by using AI (Kosmyna, et al., 2025), and while the study contains a number of methodological issues (e.g., only 54 participants), it still provides a viewpoint on some pitfalls on using AI.

While you may not agree with these thoughts and the research, I have been thinking about this for some time now. Is AI a friend or foe? When I have reviewed papers and presentations, I lose focus when I could tell they were AI rather than human generated. I’m also not saying don’t use AI; I believe AI is here to stay.

3.What do I think the future might hold in the face of AI?

As mentioned in the various examples so far, AI is accelerating faster than any technology I have encountered. “Gartner predicts 40% of enterprise apps will feature task-specific AI agents by 2026” (Choubey, 2025). Leaders are laser-focused on finding competitive gains from using AI, Automation and Machine learning and trying to free up time for employees to be creative and do their best work. In some cases, I have read in various articles (Hale, 2025; Edmondson & Chamorro-Premuzic, 2025) of organisations removing roles and replacing them with AI and automation. I believe some of this is true; however, this is often the natural evolution of the way we work within a technology driven environment.

The more we use AI to create lengthy reports, presentations and content that may feel quick and easy without considering the impact (e.g., wasted effort, repetition), the more we need leaders to step forward and set a good example based upon their organisation’s policy. I believe leaders who pilot the use of AI as a way of augmenting work and helping improve creative content will succeed in the long term. This will build trust and ensure that employees are using AI in a way that adds value.

Is AI Friend or Foe?

AI, like many other technologies, depends on how it is used. I believe that AI is both a friend and a foe, but not by default. In many scenarios, AI, automation and machine learning can be extremely powerful and a catalyst for growth and scaling efficiently. However, this catalyst often reflects the intentions and actions of the employees and leaders who deploy and use it. Employees need to avoid the dreaded “workslop” and cognitive loss, while leaders need to equip their teams with knowledge and the freedom to express themselves. We are currently in the driving seat and will determine the success or failure of AI initiatives.

References

Challapally, A., Pease, C., Raskar, R., & Chari, P. (2025). The GenAI Divide STATE OF AI IN BUSINESS 2025. MIT NANDA, 1-26.

Choubey, S. (2025, August 26). Gartner Predicts 40% of Enterprise Apps Will Feature Task-Specific AI Agents by 2026, Up from Less Than 5% in 2025. Retrieved from Gartner: https://www.gartner.com/en/newsroom/press-releases/2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026-up-from-less-than-5-percent-in-2025

Edmondson, A. C., & Chamorro-Premuzic, T. (2025, September 16). The Perils of Using AI to Replace Entry-Level Jobs. Retrieved from Harvard Business Review: https://hbr.org/2025/09/the-perils-of-using-ai-to-replace-entry-level-jobs

Hale, C. (2025, September 2). Salesforce CEO says it cut 4,000 support jobs – and replaced them with AI. Retrieved from Tech Radar: https://www.techradar.com/pro/salesforce-says-it-cuts-4-000-support-jobs-and-replaced-them-with-ai

Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., . . . Maes, P. (2025). Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X. H., Beresnitzky, A. V., … & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task. arXiv preprint arXiv:2506.08872, 1-206.

Niederhoffer, K., Kellerman, G. R., Lee, A., Liebscher, A., Rapuano, K., & Hancock, J. T. (2025). AI-Generated “Workslop” Is Destroying Productivity. Harvard Business Review, 1-5.

Pullen-Ferreira, C. (2025). Organisational Agility – The impact of resistance to change during transformation. 1-120.

Tadros, E., & Karp, P. (2025, October 05). Deloitte to refund government. Retrieved from Financial Review: https://www.afr.com/companies/professional-services/deloitte-to-refund-government-after-admitting-ai-errors-in-440k-report-20251005-p5n05p?utm_content=feed&utm_term=afr_social_eds&utm_medium=social&utm_campaign=afr&utm_source=LinkedIn#Echobox=1759711055-3

About the author, Dr. Carlos Pullen-Ferreira.

A senior leader in transformation, change, PMO, Business Analysis and strategic delivery, with over 20 years of experience across financial services, technology, airline, operations, product, commercial, supply chain and regulated industries. Carlos has held senior roles at Sage, Virgin Atlantic, Camelot (GTech), BSG and Accenture.

He has a proven track record or building high-performing teams, and leading large-scale enterprise-wide portfolios and transformation programmes. Carlos has delivered strategic outcomes through collaborative team leadership, Agile/Lean governance, coaching, and innovation.

Carlos has a Doctorate in Organisational Change, Artificial Intelligence and Communication from Durham University. Carlos is also an Adjunct Staff member at Durham University where he is an Academic Mentor and Visiting Lecturer for Organisational Change and Leadership.