AI and the Risk of Losing Human Skills – Suggestion to Tackle – Asrar Qureshi’s Blog Post #1296

AI and the Risk of Losing Human Skills – Suggestion to Tackle – Asrar Qureshi’s Blog Post #1296

Dear Colleagues! This is Asrar Qureshi’s Blog Post #1296 for Pharma Veterans. Pharma Veterans Blogs are published by Asrar Qureshi on its dedicated site https://pharmaveterans.com. Please email to pharmaveterans2017@gmail.com  for publishing your contributions here.

Credit: Tara Winstead

Preamble

This 2-part blogpost is based on a recent article by Boston Consulting Group. Link to the article at the end.

AI Is a Tool, not a Substitute for Thinking: How Organizations Can Preserve Human Intelligence

Part 2 of a Two-Part Series

Drawing on Boston Consulting Group's research, we saw that AI's greatest danger is not job loss but the gradual erosion of human judgment, critical thinking, creativity, and problem-solving when employees increasingly allow AI to think on their behalf. BCG describes this as distributed de-skilling—a collective decline in organizational capability that occurs when cognitive work is routinely delegated to AI. This should concern every CEO, manager, educator, and policymaker.

Yet the purpose of BCG's report is not to discourage AI adoption. On the contrary, the report argues that organizations can enjoy AI's enormous productivity benefits while protecting and even strengthening human capability, provided they redesign the way work is performed. The challenge is no longer whether to use AI. The challenge is how to use AI wisely.

AI Should Augment Human Intelligence

For years, technology has been promoted as a way to automate work. Generative AI certainly automates many tasks. But leaders should resist the temptation to automate thinking itself.

The organizations that will thrive in the coming decade are unlikely to be those that automate the most work. They will be those that combine AI's speed, AI's analytical capability, and uniquely human judgment. The objective should therefore be augmentation rather than substitution.

Leadership Must Create the Right Conditions

BCG argues that preventing de-skilling begins at the organizational level rather than the individual level. This is fundamentally a leadership responsibility.

Employees generally behave according to the systems leaders design. If organizations reward speed alone, employees will naturally rely heavily on AI. If organizations reward thoughtful reasoning, questioning, and sound judgment, employees will continue exercising those capabilities.

Define "AI-On" and "AI-Off" Zones

One of BCG's most practical recommendations is surprisingly simple.

Not every task should be delegated to AI.

Organizations should intentionally distinguish between AI-On Activities.

Tasks where AI creates substantial value, including summarizing documents, drafting routine communications, organizing information, automating repetitive processes, generating first drafts, coding assistance, translation, and routine data analysis. These activities free employees to focus on higher-value work.

AI-Off Activities. Some work should deliberately remain primarily human. Examples include defining strategic problems, ethical decision-making, executive succession, coaching conversations, performance evaluations, innovation workshops, complex negotiations, and decisions involving significant uncertainty.

The lesson is clear. Just because AI can perform a task does not always mean it should.

Redesign Workflows, Not Just Technology

Many organizations introduce AI by simply adding new software to existing processes. BCG suggests a different approach.

Rather than asking, "Where can we insert AI?" leaders should ask, "How should work itself change?" This is a profound distinction.

In this model, AI supports thinking; it does not replace it.

Keep Humans Responsible

One of the dangers discussed in Part 1 was declining accountability.

Every important decision should have a clearly identified human decision-maker. AI may provide recommendations, probabilities, forecasts, or alternative scenarios, but responsibility always remains human.

Technology can inform decisions. Only people should own them.

Train People to Challenge AI

Most AI training focuses on learning prompts. That is necessary, but not sufficient.

Employees must also learn how to question AI outputs, verify sources, identify hallucinations, recognize bias, detect logical inconsistencies, and evaluate recommendations critically. Critical thinking becomes even more valuable in an AI-rich environment.

Preserve the Apprenticeship Model

One issue receiving increasing attention is the impact of AI on early-career professionals.

Traditionally, junior employees learned through experience. They drafted reports, analyzed data, prepared presentations, conducted research, and received feedback from experienced colleagues.

AI now performs many of these entry-level tasks. This creates an unintended consequence. If young professionals no longer perform foundational work, how will they develop the judgment needed for future leadership?

Several experts have warned that excessive automation could weaken the pipeline that produces tomorrow's managers and executives. Organizations must therefore protect opportunities for learning—even when AI could complete the task faster.

Invest More in Human Skills

Ironically, the AI era increases the value of capabilities that machines struggle to replicate.

BCG identifies several such skills:

• empathy

• active listening

• leadership

• curiosity

• resilience

• motivation

• self-awareness

• social influence

• lifelong learning

These capabilities deserve greater, not lesser, investment. Leadership development programs should increasingly emphasize coaching, communication, ethical reasoning, collaboration, emotional intelligence, and strategic thinking.

What This Means for CEOs

For chief executives, the message is straightforward. Do not measure AI success solely through productivity.

If productivity rises while thinking declines, the organization may be accumulating cognitive debt. That debt eventually becomes expensive.

Lessons for Pharmaceutical Companies

The pharmaceutical industry offers a particularly relevant example.

AI is already transforming drug discovery, clinical trial design, pharmacovigilance, medical writing, regulatory submissions, manufacturing, and commercial forecasting. These advances are enormously valuable. Yet pharmaceutical companies must ensure that medical judgment remains human, regulatory decisions remain accountable, scientific skepticism is preserved, and ethical standards continue guiding every decision.

Patients depend upon more than algorithms. They depend upon responsible professionals.

Lessons for Education

Schools and universities face similar challenges. 

If students use AI to complete every assignment, they may obtain better grades while learning less.  Education should therefore shift its emphasis. Instead of assessing only final answers, educators should increasingly evaluate reasoning, originality, discussion, reflection, collaboration, and problem formulation.

Students should learn how to work with AI, not become dependent upon it. The purpose of education remains unchanged. It is to develop human capability.

A New Definition of Competitive Advantage

For decades, organizations competed through capital, technology, manufacturing, or scale. In the AI era, competitive advantage may increasingly depend upon something else. Organizations that preserve human judgment while fully utilizing AI will outperform organizations that merely automate work.

Technology can be purchased; human capability cannot be. That makes people, not algorithms, the ultimate source of sustainable advantage.

Sum Up

Artificial Intelligence represents one of the greatest technological opportunities in modern history. It promises extraordinary improvements in productivity, innovation, and efficiency. Ignoring AI would be a strategic mistake. But embracing AI without protecting human capability would be an even greater one.

Boston Consulting Group's report delivers a timely reminder that organizations are not simply collections of software and processes. They are communities of people whose judgment, creativity, curiosity, and leadership determine long-term success. Those capabilities must be deliberately protected through thoughtful governance, redesigned workflows, continuous learning, and a culture that values questioning as much as speed.

The future will not belong to organizations where AI does all the thinking. Nor will it belong to organizations that reject AI altogether. It will belong to organizations where artificial intelligence and human intelligence strengthen one another.

Concluded.

Disclaimers: Pictures in these blogs are taken from free resources at Pexels, Pixabay, Unsplash, and Google. Credit is given where available. If a copyright claim is lodged, we shall remove the picture with appropriate regrets.

For most blogs, I research from several sources which are open to public. Their links are mentioned under references. There is no intent to infringe upon anyone’s copyrights. If, any claim is lodged, it will be acknowledged and duly recognized immediately. 

Reference:

https://www.bcg.com/publications/2026/when-everyone-uses-ai-companies-risk-critical-skills?utm_campaign=ai&utm_content=202607_title-topsection&utm_description=top10&utm_geo=global&utm_medium=email&utm_source=esp&utm_topic=ai&utm_usertoken=CRM_ec8a706ddd1afd128c0d41808e57173ddaa23495&utm_dmid=FE18187F-5EF3-EF11-83C9-126ABB57D457&mkt_tok=Nzk5LUlPQi04ODMAAAGjFEutxi7rImc0ecONO4U4HyYXQKQFiym3_uNyQtLVx-TpaCliZJNUA9tOxcYuVYGCutySSeIdIviIUJpZKoU0Qj4eEU890S5r9ya_QeoqH3IdUZk