Tag: management

Your Managers Are Spending 60% of Their Time on Work That Doesn’t Move the Business. AI Should Have Fixed This by Now.

~ jordan ~ Leave a comment

McKinsey’s 2025 Leadership Report found that executives spend nearly 60 percent of their time on low-value tasks: meetings without outcomes, redundant reports, and reactive firefighting. A 2024 JobStreet study found that 76 percent of Filipino employees feel their leaders are too busy to connect. And a 2026 Deloitte survey found that while 85 percent of leaders say building organizational agility is critical, only 7 percent believe they are actually leading on it.

Three separate research streams, same conclusion: leaders are drowning in low-value activity while the high-value work — connecting with people, making strategic decisions, developing the team — consistently gets squeezed out by the urgent and the administrative.

AI was supposed to fix this. And in organizations that have deployed it thoughtfully and developed their managers to use it, it has. In most organizations, it hasn’t — because the manager’s calendar did not change.

The busyness that ate the strategy

Here is the pattern that plays out in organization after organization. AI automates a report that used to take three hours. The manager recovers three hours. Those three hours are not protected, redirected, or deliberately used for the high-value work that was previously crowded out. They are absorbed, within days, by the next urgent request, the next fire, the next meeting that was already in the calendar from before the AI existed.

The busyness expands to fill the space. The high-value work remains unscheduled. And six months after the AI deployment, the manager is just as overloaded as before — with different tasks filling the same amount of time, and the organization wondering why AI did not deliver the productivity gains it promised.

The missing piece: intention

AI frees time. Intention fills it with something better. And intention — the deliberate decision about what to do with recovered time — is a leadership behavior, not a technology feature. No AI system will tell a manager to use the recovered hour for a development conversation with a struggling direct report rather than clearing the inbox. That decision requires a manager who has been developed to make it, repeatedly, until it becomes the default.

This is the leadership behavior that separates organizations where AI delivers measurable value from organizations where AI delivers measurable savings that never appear in business outcomes. The savings are real. The behavior change is missing.

What the Law of Priorities says about this

John Maxwell’s Law of Priorities is blunt: activity is not accomplishment. A busy manager and a high-performing manager are not the same thing. The high-performing manager has made a deliberate choice about what deserves their best energy — and said no, actively and repeatedly, to everything else. In 2026, AI makes that choice easier than ever. But the manager still has to make it.

The specific behaviors are simple but require practice: blocking strategic time before administrative time fills the calendar; asking weekly “what high-value work am I not doing because I am busy”; using AI to handle the administrative load and then actually using the recovered time for the coaching, the thinking, and the connecting that only a human manager can do.

The LEADdaily application

A manager who builds the daily habit of protecting one high-value hour and filling it with deliberate leadership work — not firefighting, not email, not meetings that could have been a message — compounds over a quarter into a fundamentally different leadership profile. The team feels it. The outcomes reflect it.

The business case

The return on AI investment is not hidden in the technology. It is hidden in the manager’s calendar. The organization that deploys AI and also develops its managers to use recovered time intentionally will see the ROI. The organization that deploys AI and leaves manager time allocation unchanged will have spent significantly more than it needed to for marginal efficiency gains.

So the simple question: in your organization, does every manager know what they will do with the time AI gives back — and does their calendar actually show it?

Recommended reading from jordanimutan.com:

1. The Law of Priorities: Why Great Leaders Do Less — and Achieve More

2. Why Your Best People Are Always Busy — but the Business Still Feels Stuck

3. Your Company Isn’t Slow — Your Decisions Are Trapped in Manual Processes

4. The Work Is Getting Done. The Outcome Isn’t.

5. Build AI-Ready Managers

Agentic AI Is Running 40% of Your Operations. What Exactly Is a Manager’s Job Now?

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This is not a hypothetical question for 2030. IMD research from 2026 estimates that in HR, procurement, and customer operations — functions where agentic AI has deployed fastest — 40 to 60 percent of day-to-day activities are now being executed autonomously by AI systems. The humans step in for interpretation, escalation, and the interpersonal elements.

Which raises the question that most job descriptions, management training programs, and performance review systems have not yet answered: when AI is doing nearly half the work, what is a manager’s job, exactly?

What AI has taken

AI agents are now handling the work that used to require manager bandwidth: scheduling, reporting, performance monitoring, candidate screening, meeting summarization, data analysis, workflow routing, and first-draft communication. These are not peripheral tasks. They are the tasks that occupied large portions of the average manager’s day.

Their removal from the manager’s plate is not a subtraction. It is a redistribution. The time that was spent on these tasks must go somewhere — and the organizations that have not deliberately decided where it goes are watching it disappear into an expanded version of the work that remains, producing busier managers with no better outcomes.

What AI cannot take

The tasks that AI cannot automate are, without exception, the tasks that most determine whether a team succeeds over time. Sensing that a team member’s engagement is dropping before any metric confirms it. Holding a conversation that requires both honesty and care, delivered at exactly the right moment. Making a judgment call in ambiguous circumstances where the data is incomplete and the stakes are real. Building the kind of trust that makes a team willing to tell their manager what is actually going wrong, rather than what looks good on a report.

These are human leadership behaviors. They cannot be prompted, generated, or automated. And in a world where 40 to 60 percent of operational work is AI-executed, they are the primary value the manager adds.

The job redefinition most organizations have not done

Most management job descriptions, performance frameworks, and development programs were written for a world where managers spent significant time on coordination, reporting, and operational oversight. That world is ending. The new job is almost entirely about people: developing capability, building trust, making judgment calls, creating the psychological safety that unlocks team performance, and translating organizational direction into human motivation.

This is a more demanding job than the one it replaces. Not more time-consuming — but requiring deeper human skill, higher emotional intelligence, and more consistent daily practice of behaviors that are harder to develop than any technical skill.

What this means for training

The leadership development programs that serve this new reality are not the ones teaching managers to understand AI tools (though that matters). They are the ones building the specifically human capabilities that AI cannot replicate: deep coaching, courageous communication, influence without authority, accountability that does not damage trust, judgment under ambiguity.

And they must build these capabilities not through events, but through daily practice, because these are behavioral skills that only stick through repetition. A manager who practices one human leadership behavior every day, in real situations, over sixty days develops the capability the new job demands. A manager who attends a workshop and returns to unchanged habits does not.

The business case

The organizations that understand what a manager’s job is in an AI-augmented world and develop their managers accordingly will have a measurable advantage: a leadership layer that adds the value AI cannot add, while allowing AI to handle the rest. Organizations that do not will have managers who are confused about their role, underperforming on the human dimensions of it, and quietly being made redundant by the technology they were supposed to be leading.

So the question every business leader needs to answer before the next management development investment: in a world where AI runs 40 percent of operations, what specifically are you developing your managers to do — and does your training program match that answer?

Recommended reading from jordanimutan.com:

1. Build AI-Ready Managers

2. The “Invisible” CEO: Building a Startup Structure That Doesn’t Break When You Step Away

3. Lead with Context, Not Control: How Modern Leaders Inspire Performance Without Micromanagement

4. Why Your Leadership Training Isn’t Working (And What To Do Instead)

5. Leadership Micro-learning: Most Leadership Training Fails. We Help Managers Apply What They Learn Daily

The Manager Who Made AI Safe to Try Got 1.4x More from It. Here’s the Behavior That Did It.

~ jordan ~ Leave a comment

Microsoft’s 2026 Work Trend Index analyzed 20,000 AI users across ten countries and found something that should change how every organization thinks about AI adoption. The employees who got the most value from agentic AI — the ones using it frequently, confidently, and in high-impact ways — had one thing in common that had nothing to do with technology.

Their manager had made it safe to experiment with it.

When managers created psychological safety around AI experimentation, employees reported up to 20 points higher AI readiness and value. They were 1.4 times more likely to be high-frequency users of agentic AI. Not because the AI was better in their organization. Because the manager’s behavior made trying it feel less risky.

What that behavior actually looks like

The research identified four specific things managers did differently in high-AI-adoption teams. They openly used AI themselves, visibly and without defensiveness. They set quality standards for AI-assisted work, so the team knew what good looked like. They created space for experimentation, signaling that trying something that didn’t work was not a failure. And they encouraged more ambitious work redesign — asking teams to rethink how work was done, not just add AI on top of existing processes.

Each of these is a leadership behavior, not a technology behavior. None of them require technical expertise. All of them require a manager who has developed the specific daily habits that make a team feel safe enough to change how they work.

Why most AI rollouts miss this entirely

The standard AI adoption playbook focuses almost entirely on access: buy the tools, train the users, set the policies, measure the licenses. What it consistently skips is the behavioral layer directly between the tool and the team: the manager.

A team with access to every AI tool available but a manager who treats AI use with skepticism, who does not use it themselves, who has not communicated any standard for AI-assisted work, and who has not signaled that experimentation is safe — that team will underuse AI regardless of the investment. The psychological safety gap quietly consumes the technology ROI.

The 20-point readiness gap is a management problem

Twenty points of AI readiness difference between teams in the same organization, using the same tools, with the same access, separated only by the behavior of their manager — that is not a technology finding. That is a management development finding. It means the return on AI investment in any organization is directly and measurably linked to the quality of manager behavior around AI, not just the quality of the AI tools themselves.

How to build the behavior, not just the awareness

A manager who is told “create psychological safety around AI” in a workshop will nod, leave, and do approximately the same thing they were already doing. The behavior does not change because the concept was explained.

The behavior changes through specific daily practice: the manager who starts using one AI tool visibly in a team meeting this week; who asks a coaching question about what an employee tried with AI this month; who acknowledges, out loud, that they tried an AI approach that did not work and here is what they learned. These are practiced behaviors, not natural instincts, and they are built through daily repetition with real feedback — not through a workshop and a set of guidelines.

The business case

The 1.4x multiplier on high-frequency AI use is not a soft engagement metric. It is a direct measure of whether the AI investment the organization made is producing the adoption rate required to generate a return. The variable controlling that multiplier, in Microsoft’s research, is manager behavior.

Which raises the obvious question: in your organization, are the managers leading the AI adoption — or are they the reason it has quietly stalled?

Recommended reading from jordanimutan.com:

1. Build AI-Ready Managers

2. How to Master Adaptive Leadership in 2025 Without Losing Your Sanity

3. The True Leadership Currency: Why Trust Is More Valuable Than Talent

4. Leadership Micro-learning: Most Leadership Training Fails. We Help Managers Apply What They Learn Daily

5. How Teams Build Trust Through Execution

Your Managers Keep Attending Training. Their Teams Still Don’t Feel Any Different.

~ jordan ~ Leave a comment

There is a specific frustration that sits quietly in most L&D functions, and it goes something like this: the training was good. The feedback forms were positive. The managers seemed engaged. And three months later, nobody on the team can point to a single thing that changed.

This is not a new problem. It is the oldest problem in leadership development, dressed in the newest training catalog. And in 2026, it is happening to AI fluency programs at exactly the same rate it has always happened to communication skills workshops, management bootcamps, and leadership retreats.

The Transformation Paradox, as Microsoft’s Work Trend Index names it, is a systems problem: organizations are investing in individual capability while the systems, norms, and daily structures those individuals operate inside remain completely unchanged. You develop the person. The environment develops them back into their original shape.

Why the environment always wins

A manager who attends a training program on coaching and returns to a team where no one expects coaching, a manager who attends an AI fluency program and returns to workflows where AI use is optional and unmeasured, a manager who attends a communication skills workshop and returns to a culture where hard conversations are still quietly avoided — each of these managers has a new skill and an unchanged context.

The context is more powerful than the skill. The daily pressure of the job, the behavior of peers, the signals from leadership above them, the systems and workflows and norms of the team — all of these push the new behavior out and reinstate the old one within weeks. Not because the training was bad. Because a single event was never designed to overpower an environment.

What the Microsoft research found about the managers who got it right

Frontier Professionals — the employees producing the highest AI value in Microsoft’s survey of 20,000 workers — were not in organizations with better training programs. They were in environments where their manager openly used AI, set quality standards for AI-assisted work, created space for experimentation, and rewarded the reinvention of work rather than just the completion of tasks. They were twice as likely to be rewarded for reimagining how work was done, regardless of outcome.

This is not a training outcome. It is a leadership environment outcome. And it is built not through a single program but through consistent daily manager behaviors that make the trained skill the expected behavior, not the exceptional one.

The design principle that changes this

The fix is not a longer training program. It is a program with a longer tail — one that does not end when the session ends, but continues in the daily work of the manager through reinforcement, accountability, and visible modeling from the leaders above them. Sixty days of structured daily follow-through after a training event will produce more lasting behavior change than two additional days of classroom time before it.

This is the LEADdaily principle applied to training design itself: the event creates the starting point, and the daily practice after it determines whether anything actually changes.

The business case

Training that changes nothing is not a neutral investment. It is a negative one: it consumes budget, creates the expectation of change, and then fails to deliver it, which erodes the credibility of future development initiatives and makes the next L&D proposal harder to approve. The cost of ineffective training is not just the budget line. It is the accumulated organizational skepticism that makes the next real development investment harder to fund.

So before the next training program is designed or purchased, the question that determines whether it will produce any return: what happens on day 31 — and is that being designed with the same intentionality as day one?

Recommended reading from jordanimutan.com:

1. Why Your Leadership Training Isn’t Working (And What To Do Instead)

2. Leadership Micro-learning: Most Leadership Training Fails. We Help Managers Apply What They Learn Daily

3. Your Managers Keep Talking About Accountability — But No One Feels It

4. The Work Is Getting Done. The Outcome Isn’t.

5. How Teams Build Trust Through Execution

Why Leadership Training Fails After Two Days And How To Make It Stick

~ jordan ~ Leave a comment

Most leadership training does not fail inside the classroom. It fails the following Monday, when the manager returns to 47 messages, three urgent issues, and one employee who wants “just five minutes.”

The training was good.

The system after the training was weak.

That is the part many companies miss.

A two-day workshop can introduce ideas. It can create awareness. It can give managers useful tools. But it cannot build habits by itself.

Habits need repetition.

Annoying, yes. Also true.

The Problem With Event-Based Training

Traditional training often works like this:

Managers attend a session. They participate. They learn concepts. They take photos of slides. Some even promise to use the handouts, which is adorable and legally allowed.

Then they return to work.

The pressure is the same. The meetings are the same. The unclear authority is the same. The old communication habits are the same.

So the new learning fades.

Not because managers do not care.

Because the work environment keeps pulling them back to old behavior.

Training Must Move From Learning To Application

The question is not, “Did they enjoy the training?”

That is useful, but limited.

The better question is:

“What changed in how they lead?”

A manager should be able to apply the training in daily work:

  • Give clearer direction
  • Make decisions faster
  • Coach instead of only correct
  • Use AI to prepare better work
  • Communicate expectations
  • Follow through on ownership
  • Help the team focus on the right priorities

This is where many programs fall short.

They teach the idea, but they do not support the application.

AI Fluency Makes The Gap Bigger

AI is now part of the management conversation.

Managers are expected to use it, explain it, guide the team, and somehow avoid causing chaos in the process. That is not automatic.

AI fluency means managers know how to use AI for real work:

  • Drafting clearer messages
  • Summarizing meetings
  • Preparing coaching notes
  • Comparing options
  • Organizing project updates
  • Finding gaps in plans
  • Improving accuracy before sending work out

But AI fluency also means knowing the limits.

AI can help with speed.

The manager still owns the judgment.

That line has to be taught clearly.

Use A 60-Day Reinforcement System

If companies want leadership training to stick, they need reinforcement after the workshop.

A simple way is a 60-day group chat.

Not a noisy chat where everyone forwards quotes with sunset backgrounds. We have suffered enough.

A useful group chat.

One where the facilitator sends short daily mini-lessons, reminders, reflection questions, and application prompts based on the training.

For example:

  • “Today, identify one decision your team is waiting for. Decide or clarify who owns it.”
  • “Before your next meeting, use AI to prepare three discussion points. Then remove the weak ones.”
  • “Give one team member clearer expectations today.”
  • “Ask: what are we doing that looks productive but does not create results?”

Small prompts create small actions.

Small actions repeated for 60 days create behavior change.

Make It Fit The Company

Leadership training should not sound like it was copied from a textbook and sprinkled with corporate seasoning.

Every company has preferred behaviors.

Some value speed. Some value careful alignment. Some value customer focus. Some value innovation. Some value discipline. Most say they value all of them, because apparently we enjoy making posters work hard.

The point is this:

Training should match the company’s leadership expectations.

Managers should learn the behaviors the organization actually wants to see.

That is why customization matters.

What Better Training Looks Like

Better leadership training has three parts.

First, teach the essentials clearly.

Second, connect the lessons to real management situations.

Third, reinforce the behavior after the classroom.

That is the structure behind LeadDaily.

It teaches middle managers how to lead properly, how to use AI to become more productive and accurate, and how to apply the learning through a 60-day group chat after the two-day training.

The goal is not just knowledge.

The goal is behavior that survives Monday morning.

If your company wants leadership training that can be customized to your preferred leadership and behavioral expectations, DM me or message me at +63.969.600-1-006.

No magic. Just structure. Which is usually what magic looks like after the invoice.

Additional Reading From jordanimutan.com

Coaching Used to Be an Advanced Leadership Skill. In 2026, It’s the Price of Admission.

~ jordan ~ Leave a comment

There was a time when a manager who coached their team was considered exceptional. Now they are considered baseline. The workforce has changed, expectations have changed, and the organizations still treating coaching as an advanced leadership skill are falling behind in retention, engagement, and the development of the next generation of talent.

MTD Training’s 2026 research is direct on this point: coaching has moved from an advanced capability to a baseline expectation. The reason is structural, not philosophical. As AI handles more of the technical and analytical work, the remaining value of a manager is almost entirely human: growing people, building judgment, creating the conditions for a team to do its best work. Coaching is not one of those things. It is most of those things.

What the workforce expects now

The research is consistent across multiple 2026 studies: younger workers, who now make up the majority of the workforce in most Philippine organizations, do not want to be managed in the traditional sense. They want ownership of their work, clarity on what success looks like, and a manager who invests in their growth. They are less tolerant of command-and-control leadership and more likely to leave organizations where their development is neglected.

This is not a generational complaint. It is a business condition. Organizations that provide the kind of coaching-based management this workforce expects will retain talent. Organizations that don’t will spend a larger and larger proportion of their budget replacing it.

What coaching actually looks like in daily management

The misconception about coaching is that it requires scheduled sessions, formal frameworks, and significant time investment. Real coaching is far simpler and far more daily: it is asking a question instead of giving an answer, giving a direction and then letting the person figure out the path, and following up on outcomes with curiosity rather than judgment.

A manager who builds three coaching behaviors into their daily work — one question that develops thinking instead of providing information, one delegation that transfers ownership rather than just assigning a task, one debrief that focuses on learning rather than performance rating — is coaching their team. Not in a formal session. In the actual workday.

Where AI removes the last excuse

The most common reason managers give for not coaching more is time. “It’s faster to just tell them.” This is true in the short term and catastrophically expensive over twelve months, as the team learns to stop thinking and start waiting for answers. But the time objection is not entirely unreasonable.

AI removes it. A manager who uses AI to handle their administrative load recovers the time that coaching requires. More specifically, a manager who uses AI to prepare for a coaching conversation in advance — thinking through the right questions to ask, the development goals of the person they’re talking to, and the most useful outcome for the session — does this in four minutes instead of forty.

AI does not coach the team. It coaches the coach. And that is exactly the right use.

The development gap

Most managers who do not coach have not been trained to coach. They have been given a framework in a workshop, watched a demonstration, and been told to “use more coaching questions.” On Monday, they use one. By Wednesday, the pressure of the day takes over and they go back to telling. Coaching becomes a daily habit through daily practice with real feedback — not through a single workshop and good intentions.

The business case

A management layer that coaches grows its own replacement. It develops the team members who will take on more responsibility, which frees the manager for more strategic work, which grows the organization. A management layer that tells creates dependency, stunts team development, and forces the organization to hire externally for capability it should have been building internally.

So the question for any organization reviewing its retention numbers this quarter: are your managers coaching their teams, or are they answering questions that their teams should already know how to answer themselves?

Recommended reading from jordanimutan.com:

1. Lead with Context, Not Control: How Modern Leaders Inspire Performance Without Micromanagement

2. Your Managers Keep Checking Everything — And That’s Why Your Team Isn’t Thinking

3. Stop Micromanaging. Start Leading. How Systems Create Trust and Ownership

4. Build AI-Ready Managers

5. Leadership Micro-learning: Most Leadership Training Fails. We Help Managers Apply What They Learn Daily

Stop Waiting for New Hires to “Figure It Out”

~ jordan ~ Leave a comment

“Let them figure it out” sounds mature until the new hire figures out the wrong thing.

That is how companies accidentally train confusion, hesitation, poor communication, and slow execution.

New hires with less than two years of experience need structure early. Not hand-holding forever. Not spoon-feeding. Just clear expectations, practical habits, and enough reinforcement so they do not have to decode the company like an ancient scroll.

The fastest way to develop early-career talent is to stop treating onboarding as information sharing.

Treat it as preparation for real work.

New Hires Learn the System Quickly

Every company has two cultures.

The official culture.
And the actual culture.

The official culture is written in values, posters, decks, and town halls.

The actual culture is learned by watching what gets rewarded, ignored, delayed, escalated, or quietly tolerated.

New hires notice this quickly.

If managers say “take ownership” but every decision gets escalated, new hires learn escalation.

If leaders say “communicate early” but people only report when things are already on fire, new hires learn silence.

If the company says “use AI” but gives no standards, new hires learn shortcuts.

And shortcuts are exciting until the output is wrong.

This is why onboarding must teach the real behaviors the company wants to see.

Do not wait for new hires to absorb the culture by accident.
Accidents are not a development strategy.

Teach Them How to Lead Before They Have a Title

Leadership training should not begin only when someone becomes a manager.

By then, many habits are already installed.

Early-career employees need leadership behaviors now:

  • Ownership
  • Initiative
  • Clear communication
  • Follow-through
  • Accountability
  • Asking better questions
  • Managing emotions
  • Thinking before reacting
  • Helping the team move forward

They may not lead people yet, but they already lead their own work.

That matters.

A new hire who can own a task, clarify expectations, update early, and solve small problems without drama is already showing leadership.

No title needed.
No corner office required.
No dramatic LinkedIn announcement.

Give Them AI Fluency With Guardrails

AI can be a powerful accelerator for new hires.

It can help them write, summarize, research, organize, prepare, and improve their work.

But AI also creates a new risk.

A weak employee with AI can produce weak work that looks impressive.

That is a problem because managers may not catch the weakness immediately. The work sounds polished. The formatting looks nice. The sentences behave themselves.

But the thinking may be missing.

That is why AI fluency must include guardrails.

Teach new hires to use AI as an assistant, not a substitute for judgment.

A simple rule:

Use AI to help you prepare.
Do not use AI to avoid understanding.

That one sentence can save managers many future headaches. Possibly even a few facial expressions during meetings.

Replace the One-Time Lecture With Daily Application

The normal onboarding model gives new hires a lot of information at once.

Then it hopes the information becomes behavior.

That is a big hope.

A better model gives them the basics upfront, then reinforces the lessons daily for 60 days.

This can be done through a group chat where the facilitator sends short, practical lessons after the classroom session.

For example:

Day 7: How to give a useful update
Day 12: How to ask for help properly
Day 18: How to use AI to improve a draft
Day 24: How to check AI output
Day 31: How to take ownership of a task
Day 40: How to handle correction
Day 52: How to spot unclear instructions
Day 60: How to reflect on growth

This keeps the training alive during the exact period when new hires are forming habits.

That is the important part.

The first 60 days teach people how to survive in the company.
Handled well, they also teach people how to succeed.

Make the Company’s Standards Visible

Every company has preferred behaviors.

Some companies value speed.
Some value careful coordination.
Some value direct communication.
Some value hierarchy.
Some value experimentation.
Some say they value all of them, which is adorable but usually confusing.

New hires need to know what your company actually prefers.

If your culture values direct updates, teach direct updates.
If your culture values careful documentation, teach documentation.
If your culture values initiative, teach what acceptable initiative looks like.

Do not leave it vague.

Vague standards create vague performance.

And vague performance creates meetings. Many meetings. The kind with titles like “alignment discussion” and “quick sync” that are neither quick nor a sync.

The Better Way

The better way is simple:

Train new hires in behavior.
Train them in AI fluency.
Train them in workplace judgment.
Reinforce the lessons for 60 days.
Customize the standards to your company.

That is how early-career employees become productive faster.

Not by magic.
Not by motivational speeches.
By design.

That is what Career Launchpad is built for. It is an onboarding program that prepares new hires to behave, communicate, lead themselves, and use AI more productively from the start. It can also be adjusted to match the leadership and behavioral preferences of the company.

If this sounds useful for your team, DM me or message me at +63.969.600-1-006.

Additional Reading From jordanimutan.com

  1. Clarity Is Uncomfortable. That’s Why It’s Rare.
  2. The Real Reason Decisions Keep Moving Up
  3. The System Always Knows Who Really Decides
  4. Speed Dies When Authority Is Unclear
  5. You Don’t Have a Performance Problem. You Have an Ownership Gap

Your Managers Drive 70% of Employee Engagement. So Why Is Their Own Engagement Falling?

~ jordan ~ Leave a comment

Gallup has been saying it for years: managers account for 70% of the variance in employee engagement. Every organization knows this statistic. Very few have drawn the obvious conclusion from it: if your managers aren’t engaged, your employees can’t be either — no matter how good the culture programs, the benefits, or the town halls are.

The 2025 Gallup State of the Global Workplace report found that manager engagement is declining. The same layer of the organization responsible for most of the human experience at work is itself experiencing less meaning, less connection, and more pressure than ever. This is not a morale problem. It is a structural leadership development problem — and it is quietly undermining every other people initiative in the organization.

Why manager engagement is falling

Middle managers in 2026 are being asked to do more than any previous generation of managers was designed for. Integrate AI into team workflows. Support burned-out employees. Meet escalating executive expectations. Navigate hybrid teams. Develop their people. Deliver results. Do all of this while managing their own workload with no reduction in scope.

Most were promoted into management without formal training. Most have never received consistent coaching or development since. Most are evaluated on their team’s output, not on the quality of their leadership behaviors. And most operate in organizations that tell them people are the priority but measure them primarily on tasks and numbers.

The gap between what the role demands and what the organization provides for it is the exact space where engagement goes to die.

The leadership trap nobody talks about

The managers who disengage don’t stop working. They stop developing. They stop investing emotionally in the outcomes. They shift from leading their team to managing through their team — communicating what’s required, tracking what’s submitted, escalating what’s unclear. The team still functions. But it doesn’t grow, because the person who is supposed to develop it has stopped being developed themselves.

This is contagious. A disengaged manager produces a disengaged team, not through any specific act, but through the slow withdrawal of the attention, energy, and belief that make leadership real.

What actually re-engages managers

Not a team-building day. Not a survey. Not a town hall where leadership thanks everyone for their hard work. What re-engages managers is the same thing that engages any professional: feeling that they are growing, that their judgment is respected, that their work produces visible results, and that someone above them is paying attention to their development, not just their output.

LEADdaily is designed around this insight: when managers practice daily leadership behaviors and see those behaviors produce real outcomes for real people, engagement follows naturally. Not because the program is inspirational, but because competence and impact are intrinsically motivating. A manager who gets better every day at something that matters has a reason to show up that no benefits package can replicate.

Where AI creates a unique opportunity

AI tools can return hours to a manager’s week that were previously lost to administrative work. But the real opportunity is what those hours can be used for: development, reflection, meaningful team interactions, and the strategic work that makes management feel like leadership rather than logistics. This only happens if the manager has been intentionally developed to use that time for growth — not just to fill it with more administration.

The business case

A disengaged manager costs an organization an engaged team, multiplied by everyone on that team, sustained over however long the disengagement lasts. The math is not complicated. The investment required to re-engage a manager who is already skilled is a fraction of the cost of hiring and developing their replacement.

So before your organization runs its next employee engagement survey, ask the harder question: when did we last genuinely invest in the development and engagement of the people running the engine?

Recommended reading from jordanimutan.com:

1. Leadership Micro-learning: Most Leadership Training Fails. We Help Managers Apply What They Learn Daily

2. Why Your Best People Are Always Busy — but the Business Still Feels Stuck

3. The True Leadership Currency: Why Trust Is More Valuable Than Talent

4. Your Managers Keep Talking About Accountability — But No One Feels It

5. Build AI-Ready Managers

You Let Your Managers Teach Themselves AI. Here’s the Bill Coming Due.

~ jordan ~ Leave a comment

Letting your managers “figure out AI on their own” feels efficient right now. It will cost you a lot more later, and the bill arrives quietly — as inconsistency, not as a single visible disaster.

Most companies didn’t choose this on purpose. AI tools showed up fast, budgets for formal training lagged behind, and managers did what capable people do when nobody gives them a system: they experimented. Some became power users. Others avoided the tools out of caution or quiet anxiety. A few used AI in ways that created real risk nobody noticed until much later. No one designed this outcome. It just happened, by default, in thousands of companies at once.

Why self-taught AI use feels fine until it isn’t

A self-taught manager who’s curious and careful might genuinely get good results. That’s the trap — it works often enough to feel safe. The problem isn’t any single manager’s skill. It’s the variance across an entire management layer, where every manager is operating on a different, untested understanding of what the tool can and can’t do.

One manager uses AI thoughtfully to draft fair, well-reasoned feedback. Another feeds confidential team data into a tool without realizing the privacy implications. A third doesn’t trust AI at all and quietly tells their team to avoid it, undercutting company strategy without anyone in leadership knowing. Same company, three completely different outcomes, and not one of them was trained on purpose.

The real cost isn’t a scandal. It’s inconsistency.

Most companies worry about the dramatic version of this risk — a data leak, a biased decision, a public mistake. Those things matter, and they happen. But the quieter, more expensive cost is consistency itself. When every manager’s AI judgment is self-taught, the business has no reliable floor for how decisions get made, how feedback gets written, or how risk gets assessed. Two employees on two different teams can get wildly different treatment, not because of policy, but because their managers learned AI differently from a YouTube video and a Slack thread.

That inconsistency erodes trust slowly. Employees notice when one manager’s decisions feel fair and well-supported while another’s feel arbitrary. They rarely connect it to “uneven AI training,” but that’s often exactly what’s underneath it.

Why “just send them a tools workshop” doesn’t close the gap

A single AI tools session teaches everyone the same features. It does not teach everyone the same judgment, and judgment is precisely where the inconsistency lives. Two managers can sit through the identical workshop and walk away with completely different instincts about when to trust the output, when to double-check it, and when not to use AI at all. Without structured practice and feedback on those judgment calls specifically, the variance survives the training untouched.

This is the same gap that has made leadership training disappoint companies for years: a one-day event creates temporary alignment in the room and almost no lasting alignment in daily behavior. AI just raises the stakes, because the inconsistent behavior now touches more decisions, faster, than it used to.

What actually closes the gap

The fix isn’t banning self-directed learning — curious managers should keep exploring. The fix is giving every manager a shared, practiced baseline: the same core judgment calls, practiced the same way, reinforced over weeks instead of taught once. Not just “here’s how the tool works,” but “here’s how we decide what to trust, what to double-check, and what never goes near AI in the first place” — built into real work, not a slide deck.

Done well, this doesn’t slow managers down. It gives the curious ones a stronger foundation and gives the cautious ones enough confidence to finally start using the tools the company already paid for.

The business case

Inconsistent AI judgment across your management layer is a hidden cost sitting on your balance sheet right now, even though no line item says so. It shows up as uneven decisions, slower adoption, and quiet risk nobody flagged because nobody was responsible for flagging it. A shared, practiced standard turns that hidden cost into a visible asset: a management team that uses AI the same way, for the same reasons, with the same judgment — no matter who’s reviewing the work that day.

So before assuming your managers’ self-taught AI skills are good enough, ask the question that actually matters: if every manager in your company is improvising their own AI judgment right now, do you actually know what’s running your business?

Recommended reading from jordanimutan.com:

1. Build AI-Ready Managers

2. Why Your Leadership Training Isn’t Working (And What To Do Instead)

3. Leadership Micro-learning: Most Leadership Training Fails. We Help Managers Apply What They Learn Daily

4. Your Managers Keep Talking About Accountability — But No One Feels It

5. The “Invisible” CEO: Building a Startup Structure That Doesn’t Break When You Step Away

Your Manager Can Prompt ChatGPT Like a Pro. They Still Can’t Coach Their Team Through a Hard Conversation.

~ jordan ~ Leave a comment

Here’s an uncomfortable fact: being good at AI and being good at leading people are not the same skill, and most companies are accidentally training only one of them.

A manager who can write a flawless prompt, automate a report, and summarize a meeting with AI in seconds can still freeze up the moment a direct report needs honest, difficult feedback. The tool got smarter. The manager’s hardest job didn’t get any easier — and in some ways, it got harder, because now there’s a new layer of decisions about when to trust AI and when to trust their own judgment.

AI fluency is necessary. It is not sufficient.

There’s no debate that managers need to understand AI now. It touches hiring, performance reviews, planning, and daily output. A manager who doesn’t understand what these tools can and can’t do will either avoid them entirely or trust them too blindly — both are costly mistakes.

But AI fluency answers the question “what can this tool do.” It says nothing about “how do I lead a human being who is anxious, defensive, or disengaged.” Those are two entirely different muscles, and building one does not automatically build the other.

Where this shows up in real teams

Picture a manager using AI to draft fair, well-structured performance feedback for an underperforming employee. The document is excellent — clear, specific, professional. Then the manager has to deliver it in person, watch the employee’s face fall, and navigate the conversation that follows without becoming defensive or backing down on accountability.

No AI tool does that part. That conversation is still entirely human, and it’s exactly the kind of skill that most companies have under-trained for years — long before AI ever entered the picture. Add a new technology layer on top of an existing leadership skills gap, and the gap doesn’t shrink. It just becomes more visible, faster.

Why companies keep solving the wrong half of the problem

Most corporate AI rollouts focus almost entirely on tool literacy: how to prompt, how to automate, how to save time. That’s the easier half to teach, because it’s mechanical and demonstrable in an afternoon.

The harder half — delegation, coaching, hard conversations, accountability without damaging trust — takes longer to build and is harder to put on a slide. So it quietly gets skipped, and companies end up with managers who are AI-fluent but no more capable of leading their teams than they were a year ago.

This is backwards. AI was supposed to free up time for the human parts of management. Instead, in many companies, it’s just compressing the mechanical work and leaving the human work exactly as under-resourced as before.

What actually works: train both, on purpose

The fix is treating AI fluency and leadership behavior as two connected skills that need to be built together, not one as a substitute for the other. Managers need real practice with AI tools, yes — but tied directly to the leadership moments where it matters: using AI to prep for a hard conversation, not to avoid having it; using AI to spot a coaching opportunity, not to skip the coaching itself.

This only works through repeated application on real situations, not a one-time demo. A manager who tries this once in a workshop and never practices it again will default right back to the conversations they were already avoiding before AI showed up.

The business case

A team led by an AI-fluent manager who still can’t coach, delegate, or hold a hard conversation will hit a ceiling fast — the tools will speed up the easy work and leave the hard work, the work that actually drives engagement and retention, untouched. A team led by a manager who’s built both skills together gets the full value: faster execution and stronger leadership, at the same time.

So the real question isn’t whether your managers can use AI. It’s whether AI training is making them better leaders, or just better typists.

Recommended reading from jordanimutan.com:

1. Build AI-Ready Managers

2. Your Managers Keep Talking About Accountability — But No One Feels It

3. Shared Responsibility Is Usually a Leadership Shortcut

4. Why Your Leadership Training Isn’t Working (And What To Do Instead)

5. Leadership Micro-learning: Most Leadership Training Fails. We Help Managers Apply What They Learn Daily