Tag Archives: upskilling

Career Development at Its Best

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Career Development at Its Best

GUEST POST from Geoffrey A. Moore

A colleague recently forwarded me an article about upskilling one’s team. I am on board with the first part—innovating from within—but I am not comfortable with the concept of “upskilling.” Here’s why.

Upskilling implies that the challenges you face lend themselves to known skilled responses. Combined with the idea of training, it also implies that you have that skills knowledge already in-house and simply need to transfer it to a new cohort. I can see both of these ideas being applicable to technical work, but I don’t think they reflect the realities of knowledge work. There, instead, I think we need to substitute learning for training and experience for upskilling.

Whereas training puts the responsibility for a successful outcome on the trainer, learning puts it on the learner. In the world of knowledge work, that’s where it has to sit. We need to develop ourselves—no one else can do it for us. But we need experience to do so, and this is where managers can have a big impact. It is not the training we give our teams but rather the assignments we entrust to them that let them build new muscles.

Assigning an inexperienced person to a new challenge is always a risk—for them, for their manager, and for the customer of the work to be done. Unfortunately, without risk, there is no learning. There is no risk-free way to learn. So the manager’s goal is to create opportunity while mitigating risk.

One of the best means for so doing is assigning people the role of the Single Accountable Leader (SAL). The need for a SAL arises in any cross-functional initiative where hierarchy of authority is replaced by team collaboration. Just as a football team needs a quarterback to run a play that involves 11 people collaborating toward one outcome, so does a cross-functional initiative need a single accountable leader to be the focus of decision-making as the team adapts to unfolding events. This person need not be an expert. They need to be vigilant. They need to stay on top of things. They need to inquire and inspect, to detect when the effort is going off course, to focus the team on redirecting it, to get counsel from their mentors, and to escalate issues that are beyond their ability to address. Most of all, they need to care.

When people care, they learn. They go the extra mile. They bring out the best in others. And in so doing, they build the new muscle that will qualify them for a larger role in the enterprise. This to me is career development at its best. The SAL assignment is the most precious gift that managers and mentors can bestow upon their charges. I hope you can take advantage of it.

That’s what I think. What do you think?

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Preparing Your Workforce for Collaborative Intelligence

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Upskilling for the AI Era

Preparing Your Workforce for Collaborative Intelligence

GUEST POST from Chateau G Pato

The rise of Artificial Intelligence is not a distant threat looming on the horizon; it is the fundamental reality of business today. Yet, the conversation is often dominated by fear—the fear of job replacement, of technical obsolescence, and of organizational disruption. As a human-centered change and innovation thought leader, I argue that this narrative misses the most profound opportunity: the chance to redefine the very nature of human work. The true imperative for leaders is not to acquire AI tools, but to upskill their human workforce for a symbiotic partnership with those tools. We must shift our focus from automation to Collaborative Intelligence, where the strength of the machine (speed, data processing) complements the genius of the human (creativity, empathy, judgment).

The AI Era demands a strategic pivot in talent development. We need to move past reactive technical training and invest in the skills that are uniquely human, those that machines can augment but never truly replicate. The future of competitive advantage lies not in owning the best algorithms, but in cultivating the workforce most skilled at collaborating with algorithms. This requires a shift in mindset, skills, and organizational design, ensuring that every employee — from the frontline associate to the senior executive — understands their new role as an AI partner, strategist, and ethical steward.

The Three Pillars of Collaborative Intelligence

Preparing your workforce for the AI era means focusing on three critical, human-centric skill areas that machines will struggle to master:

  • 1. Strategic Judgment and Empathy: AI excels at calculation, but it lacks contextual awareness, cultural nuance, and empathy. The human role shifts to interpreting the AI’s output, exercising ethical judgment, and translating data into emotionally resonant actions for customers and colleagues. This requires deep training in human-centered design principles and ethical decision-making.
  • 2. Creative Problem-Solving and Experimentation: The most valuable new skill is not coding, but prompt engineering and defining the right questions. Humans must conceptualize new use cases, challenge the AI’s assumptions, and rapidly prototype new solutions. This demands a culture of psychological safety where continuous experimentation and failure are encouraged as essential steps toward innovation.
  • 3. Data Literacy and AI Stewardship: Every employee must become literate in data and AI concepts. They don’t need to write code, but they must understand how the AI makes decisions, where its data comes from, and why a result might be biased or flawed. The human is the ethical backstop and the responsible steward of the algorithm’s power.

“The AI won’t take your job; a person skilled in AI will. The upskilling challenge is not about the technology; it’s about the partnership.” — Braden Kelley

Case Study 1: The Global Consulting Firm – From Analyst to Interpreter

The Challenge:

A major global consulting firm faced the threat of AI automation taking over their junior analysts’ core tasks: data aggregation, slide creation, and basic research. They realized that their competitive edge was not in performing these routine tasks, but in their consultants’ ability to synthesize, communicate, and build client trust—all uniquely human skills.

The Collaborative Intelligence Solution:

The firm launched a massive internal upskilling initiative focused on transforming the junior analyst role from “data processor” to “AI interpreter and client strategist.” The training focused heavily on non-technical skills: narrative storytelling (using AI-generated data to craft compelling client stories), ethical deliberation (identifying bias in AI-generated recommendations), and active listening (improving client empathy). AI was positioned not as a replacement, but as an instant, tireless research assistant that handled 80% of the routine work.

The Human-Centered Result:

By investing in human judgment and communication, the firm increased the value of its junior workforce. Consultants spent less time creating slides and more time on high-impact client interactions, leading to stronger relationships and more innovative solutions. This shift proved that the ultimate value-add in a service industry is the human capacity for strategic synthesis and trustworthy communication — skills that thrive when augmented by AI.

Case Study 2: Leading Retail Bank – Embedding AI into Customer Service

The Challenge:

A large retail bank implemented AI chatbots and automated routing systems to handle routine customer inquiries, intending to reduce call center costs. However, customer satisfaction plummeted because complex or emotionally charged issues were being mishandled by the automation. The human agents felt demoralized, fearing redundancy.

The Collaborative Intelligence Solution:

The bank pivoted its strategy, creating a new role: the Augmented Human Agent. The human agents were upskilled in two key areas. First, they received intensive training in emotional regulation and conflict resolution to handle the high-stress, complex calls that the AI flagged and escalated. Second, they were trained in “AI tuning” — learning to review the chatbot’s transcripts, identify common failure points, and provide direct feedback to the AI development team. This turned the agents from passive recipients of technology into active partners in its improvement.

The Human-Centered Result:

This approach restored customer trust. Customers felt valued because their most difficult problems were routed quickly to a highly skilled, emotionally intelligent human. Employee engagement improved because agents felt empowered and recognized as essential collaborators in the bank’s digital transformation. The result was a successful blend: AI handled the volume and efficiency, while highly skilled humans handled the emotion and complexity, achieving both cost savings and higher customer satisfaction.

Conclusion: The Future of Work is Partnership

The AI Era is not about a technological race; it is about a human race to redefine skills, value, and purpose. The most forward-thinking leaders will treat AI deployment as a catalyst for human capital development. This means shifting budget from outdated legacy training programs to investments in judgment, ethics, creativity, and empathy. The future of work is not about the “Man vs. Machine” conflict, but the Man with Machine partnership.

Your competitive advantage tomorrow will be determined by how effectively your people can collaborate with the intelligent systems at their disposal. By focusing your upskilling efforts on the three pillars of Collaborative Intelligence, you ensure that your workforce is not just surviving the AI revolution, but actively leading it—creating a future that is not just efficient, but fundamentally human-centered and more innovative.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

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The Neuroscience of Unlearning

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Making Room for New Operating Systems

Why unlearning is the hidden challenge of transformation and how leaders can design environments that enable cognitive renewal.

The Neuroscience of Unlearning

GUEST POST from Chateau G Pato
LAST UPDATED: January 1, 2026 at 12:54PM

In our current world, we are witnessing a phenomenon that most traditional business models were never designed to handle: the absolute necessity of erasure. For decades, the mantra of the corporate world was “continuous learning.” We built massive infrastructures dedicated to upskilling, reskilling, and the acquisition of new knowledge. But in 2026, as agentic AI and autonomous systems begin to handle the transactional “grunt work” of innovation, we are discovering that the true bottleneck to progress isn’t a lack of new information. It is the overwhelming presence of old information.

To move forward, we must understand the Neuroscience of Unlearning. We aren’t just updating software; we are attempting to overwrite deeply encoded biological “operating systems” that have been reinforced by years of success, survival, and habit. As a globally recognized innovation speaker, I frequently remind my audiences that innovation is change with impact, and you cannot have impact if your mental real estate is fully occupied by the ghosts of yesterday’s best practices.

“The hardest part of innovation is not the learning of new things, but the unlearning of old ones. We are trying to run a 2026 AI-driven OS on a 1995 hierarchical mindset, and the biological friction is what we misinterpret as resistance to change.” — Braden Kelley

The Biology of Cognitive Inertia

Our brains are masterpieces of efficiency. Through a process called Long-Term Potentiation (LTP), the neural pathways we use most frequently become “paved” with myelin, a fatty substance that speeds up electrical signals. This is why a seasoned executive can make a complex decision in seconds—their brain has built a high-speed expressway for that specific pattern of thought. However, this efficiency is also a cage. When the environment changes—as it has so drastically with the rise of decentralized work and generative collaboration—those expressways lead to the wrong destination.

Unlearning requires Long-Term Depression (LTD), the biological process of weakening synaptic connections. Unlike learning, which feels additive and exciting, unlearning feels like a loss. It is metabolically expensive and emotionally taxing. It requires us to activate our metacognition—our ability to think about our thinking—and consciously inhibit the dominant neural networks that tell us, “this is how we’ve always done it.” This is where the Corporate Antibody lives; it isn’t just a cultural problem, it is a neurological one.

Case Study 1: The Kodak “Comfort Trap”

The Challenge: Despite inventing the first digital camera in 1975, Kodak famously failed to capitalize on the technology, eventually filing for bankruptcy in 2012. Many attribute this to a lack of technical foresight, but the root cause was a failure of unlearning.

The Cognitive Friction: Kodak’s “Operating System” was built on the chemical process of film and the high-margin razor-and-blade model of silver-halide paper. Their leaders were neurologically “wired” to see the world through the lens of physical consumables. Digital photography wasn’t just a new tool; it required unlearning the very definition of their business. They couldn’t “depress” the neural pathways associated with film fast enough to make room for the digital ecosystem.

The Lesson: Knowledge is a power, but it can also create blind spots. Kodak’s experts were so good at the old game that they were biologically incapable of playing a new one.

Upgrading the Human OS

In 2026, the shift is even more profound. We are unlearning the concept of “work as a location” and “management as oversight.” Leading organizations are now focusing on Human-AI Teaming, where the human role shifts from originator to curator. This requires a radical unlearning of individual ego. To succeed today, a leader must unlearn the need to be the “smartest person in the room” and instead become the most “connective person in the network.”

Case Study 2: Microsoft’s Growth Mindset Transformation

The Challenge: Prior to Satya Nadella’s tenure, Microsoft was defined by a “know-it-all” culture. Internal competition was fierce, and silos were reinforced by a psychological contract that rewarded individual brilliance over collective innovation.

The Unlearning Strategy: Nadella didn’t just introduce new products; he mandated a shift to a “learn-it-all” (and “unlearn-it-all”) philosophy. This was a Human-Centered Change masterclass. By prioritizing psychological safety, he allowed employees to admit what they didn’t know. This lowered the “threat response” in the brain, making it neurologically possible for employees to dismantle old competitive habits and embrace a cloud-first, collaborative mindset.

The Result: By unlearning the “Windows-only” worldview, Microsoft reclaimed its position as a market leader, proving that cultural transformation is, at its heart, a massive exercise in neural rewiring.

Leading Companies and Startups to Watch

As we navigate 2026, watch companies like Anthropic, whose “Constitutional AI” approach is forcing us to unlearn traditional prompt engineering in favor of ethical alignment. BetterUp is another key player, using behavioral science and coaching to help employees “unlearn” burnout-inducing habits. In the productivity space, Atlassian is leading the way by unlearning the traditional office-centric model and replacing it with “Intentional Togetherness,” a framework that uses data to determine when physical presence actually drives value. Also, keep an eye on startups like Tessl and Vapi, which are redefining the “OS of work” by automating the transactional, forcing us to unlearn our reliance on manual task management and focus instead on high-value human creativity.

“Unlearning feels like failure to the brain, even when it is the smartest move available.” — Braden Kelley

Conclusion: Making Room for the Future

To get to the future first, you must be willing to travel light. The “useful seeds of invention” are often buried under the weeds of outdated assumptions. As you look at your own organization or career, ask yourself: What am I holding onto because it made me successful in 2020? What “best practices” have become “worst habits” in a 2026 economy? The Neuroscience of Unlearning tells us that while it is difficult to change, it is biologically possible. We simply need to provide our brains—and our teams—with the safety, time, and intentionality required to clear the path for a new operating system.

Frequently Asked Questions

Why is unlearning harder than learning?

Learning is additive and often triggers the reward centers of the brain. Unlearning requires weakening existing, myelinated neural pathways (Long-Term Depression), which the brain perceives as a loss or a threat. It is more metabolically expensive and emotionally difficult to “delete” than to “save.”

What is a “Corporate Antibody”?

It is the natural organizational resistance to change. Just as a biological antibody attacks a foreign virus, an organization’s existing culture, processes, and “successful” mental models will attack new ideas that threaten the status quo. Successful unlearning requires “disarming” these antibodies through psychological safety.

How can a leader encourage unlearning in their team?

Leaders must model vulnerability. By moving from a “know-it-all” to a “learn-it-all” mindset, they create a safe space for others to question outdated habits. Using frameworks like the Change Planning Toolkit™ helps make this transition structured rather than chaotic.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credits: Google Gemini

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