⚡️ Superagency

Let’s talk about The Superagency Advantage…

If you haven’t heard of this before, it’s a concept by Reid Hoffman that describes a state where AI amplifies human capabilities, leading to enhanced creativity, productivity, and positive impact.

When we look ahead one thing is clear: the businesses and individuals who embrace AI now will be the ones leading the future.

Hard stop.

Here’s what’s possible (and what’s coming) with AI in the workplace:

🔹 Productivity Boost: AI could automate up to 70% of non-value-added tasks, unlocking $2.6T-$4.4T in productivity.

 🔹Workforce Change: 75% of business leaders expect workforce shifts due to AI, from re-skilling to hiring.

🔹Impact: AI-enabled companies could see a 40% productivity boost and 5-10% revenue growth.

🔹Adoption Gap: While 94% see AI as essential, only 23% feel ready for full adoption.

🔹Re-skilling: 50% of workers will need re-skilling by the end of 2025 to thrive alongside AI, while demand for low-skill, repetitive roles is expected to decrease. Holy … yes, that’s HALF.

The below report helps to visualize some of the biggest key elements and this issue is all about the impact ahead of these numbers.

I opted to pull the strongest topics to go deeper on so we can get a full feel for what this means.

🤫 Employees Are Using AI More Than Leaders Think

But is it really that surprising?

Key Facts

• 🤔 Underestimated Usage: Leaders estimate that only a small fraction of employees use AI daily, but in reality, it’s much higher.
• 🚀 Changing Landscapes: The majority of employees believe AI will significantly transform their work soon.
• 🎓 Desire for Training: Many employees are eager to get up to speed with AI but feel their companies aren’t providing enough support.

You’ve heard this story before.

Employee is hired for something they enjoy. Employer celebrates them doing the thing they were hired to do. Employee gets tired of the same things. Employer still needs them to do thing they were hired for. Employee doesn’t understand why they can’t “get ahead” and employer kinda-sorta-maybe tries to support them but needs them to do the thing and just be ok with it. No one is winning. 

Enter 2025, where things have the possibility to change in ways we hardly saw coming.

Now, many managers are shocked to discover that several of their team members are quietly using AI tools to streamline their tasks, ideate on new ones or automate what they don’t want to do anymore—without any guidance or policy from the company. 

So, what’s going on here?

Employees are finding ways to be more efficient on their own.

There’s a gap between what leaders think is happening and what’s actually happening on the ground. Employees are excited about AI’s potential and are already experimenting, while leadership might be lagging in supporting this shift.

Is it fear?

Is it lack of attention?

Or is it just that employers don’t have the time of day to consider the shift while employees want to hedge the fear of it replacing them?

There’s a lot of questions here but here’s why it matters.

This dramatic gap shows that employees are far ahead of leadership assumptions in integrating generative AI into their daily work. 

Over 70% of employees believe that in just two years, Gen AI will transform at least 30% of their tasks, signaling a rapidly evolving work environment that many leaders may be underestimating. 

Without proper guidance, employees experimenting with AI on their own may face significant challenges, from security risks to burnout as they navigate this shift without the right support.

Here’s my advice:

• Open the Conversation: Leaders should proactively ask their teams about their use of AI tools.
• Provide Training: Offer learning opportunities so employees can use AI effectively and responsibly.
• Develop Policies Together: Create guidelines that help everyone understand best practices for AI use in the workplace.

In fact, I’ve been thinking about holding trainings for things like this. Is it something you’d be interested in? Leave a comment and let me know if so!

Trusting AI is a team effort. 

By acknowledging the proactive steps your employees are taking and providing the necessary support, everyone can benefit from AI’s innovation drive and stay ahead of the curve.

🚧 Companies Keep Spending $ On AI Despite Setbacks

Generative AI is seeing massive investment, but are companies actually getting value from it? The numbers suggest otherwise.

Key Facts

• 💸 Rising Budgets: Many organizations intend to boost their AI investments, even while struggling to show a clear return on investment (ROI).
• ⏳ Slow Progress: On average, it takes over a year to move from AI pilot projects to full-scale implementation.
• 📏 Measurement Gaps: Most companies don’t have effective ways to measure the value of their AI investments.

A paradox is unfolding in AI adoption: billions are being spent, yet operational success could remain elusive.

But what’s holding them back?

• Lack of Clear Goals: Without specific objectives, it’s hard to measure success.
• Technical Hurdles: Integrating AI into existing systems isn’t always straightforward.
• Talent Shortage: There may not be enough skilled people to drive these projects forward.
• Unknown outcomes: How do we measure success on something that’s (likely) never been done before?

Companies are eager to integrate AI but are struggling with outdated systems, ROI tracking failures, and a major skills gap. 

Over 70% of projects stall due to talent shortages, and 83% of enterprises lack a clear way to measure AI’s value.

✅ The Reality Check

Businesses chasing AI hype without a clear execution plan are burning cash. 

The average enterprise wastes $19M annually on underutilized AI infrastructure. 

Nineteen MILLION! 🤑 

Meanwhile, regulatory risks are rising, with 44% of compliance projects facing scrutiny.

So, what’s the fix?

• Invest smarter: High-performing firms allocate 73% of their AI budget to proven, high-ROI use cases.
• Fix technical debt: Prioritize robust data pipelines over flashy AI models.
• Upskill teams: AI-mature companies have fluid workforces, constantly rotating talent across AI projects.

Right now, companies are throwing money at AI in a FOMO-driven race. But the winners will be those who move from reckless spending to precision execution. 

By 2026, those who master AI maturity will own 83% of industry-specific AI advantages—while the rest fund their own disruption.

This is also the biggest reason I keep this newsletter alive every week, and advise with the work we do at Bara AI. you wouldn’t go on a roadtrip without first looking at the map & how to get there. 

Would you?

🚦 Is Leadership Really Ready for AI?

C-suite leaders are 2.4x more likely to see employees as the barrier to AI adoption—while overlooking their own leadership gaps.

Key Facts

• 🔍 Misdiagnosed Problem: 94% of employees are actively adopting AI tools, yet 72% of organizations lack clear policies to support them.
• 📉 Training Paradox: Nearly half of employees say AI training is the #1 success factor, but only 9% of companies have scaled up-skilling programs.
• ⏳ Productivity Drain: Teams using unsupported AI tools lose 14 hours per week troubleshooting instead of working efficiently.

The cost of misalignment is adding up fast. 💰

With 32% of AI usage happening through unauthorized tools, security and compliance risks are growing. 

Without clear guidance, AI adoption remains fragmented, leading to slower ROI and wasted potential. 

On top of that, 68% of employees worry that leadership’s inaction on AI will stall their career growth, creating frustration and uncertainty in the workplace.

The solution starts with leadership setting the tone. When executives actively use AI tools—like Adobe’s leadership team did to cut meeting prep time—adoption spreads naturally. 

But it’s not just about using AI; it’s about making it work for real business goals. 

Companies that tie AI initiatives to measurable outcomes see adoption accelerate by 67%. 

Training also can’t be an afterthought—AI-mature organizations dedicate 70% of their AI budgets to up-skilling and alignment rather than chasing the latest flashy tool. 

Experimentation needs guardrails, not roadblocks.

AI “safety nets,” like compliance review teams and low-risk experimentation budgets, allow companies to innovate without unnecessary risks.

🚀 The Bottom Line

Companies that fix AI leadership alignment see:

• 89% faster AI ROI
• 3.1x higher employee retention
• 76% fewer redundant AI tools

Employees are already building AI momentum. Will leadership catch up—or keep getting in their way?

These topics are massively important to me which is why today’s overview was meant to paint the clearest picture possible for you to consider.

Weather you’re an employee, employer, or just someone who cares about where the opportunities are.. we have to take the shift in priorities seriously or risk falling behind FAST.

If you want to jump in but don’t know where to start…

📍You’re in the right place at the right time. Here’s how to get the most out of AI.

Join the conversation in my Slack community where we talk about these topics as a group and keep a pulse on everything happening.

I run this incredible private community for thought leaders like you who are interested in AI development and implementing it into their own personal and professional lives.

Right now, it’s open for enrollment. 

• 🤝 Networking & Collaborations
• 🧠 AI Insights & Tools Showcase
• 📆 Monthly Q&A “Office Hours” with me
• 📞 A 1:1 Welcome Call for us
• …and more!

Check it out here: https://fastfoundations.com/slack 🔗