Intro

Old MacDonald had a farm… and today’s executives have an AI farm. But not every “animal” is the same. Most leaders are working with Generative AI (GenAI) — powerful but limited. Emerging quickly is Agentic AI — systems that can take initiative. And still further out is General AI (AGI) — the wildcard of AI’s future.

We are going to rock our first 5 Bytes edition (tech = bytes instead of bites…pretty clever!). Coming off of Auxiom’s first-ever Auxiom Community Appreciation Event (ACA), I’m feeling technologically inspired. Those of you who attended heard from amazing speakers like Scott Schoeneberger of Bluewater Tech, Mykolas Rambus of Hush AI, our own Marcus Rebelo (CISO & Head of AI at Auxiom), and Lt. Col. USMC (ret.) Robert J. Darling !

This edition breaks down the three levels of AI, the costs they bring, and the leadership role only you can play.

Byte 1: Generative AI — The Draft Machine on the Farm

On today’s AI farm, Generative AI is like the scribes (those smart little brainiacs) in the barn — fast, tireless, and able to crank out first drafts all day long. (Jackie here turned me on to Suits—the old one—and this is reminding me of the associates at Pearson Hardman.)

Think ChatGPT, Microsoft Copilot, Claude, Gemini.

What it does well today:

• Drafts contracts, memos, proposals, marketing copy
• Summarizes meetings, emails, reports
• Provides quick explanations and answers

Limits:

• Limited or no persistent memory across sessions (some tools offer limited recall)
• No decision-making ability
• Not built for multi-step workflows

👉 Exec takeaway: GenAI is the barnhand with a notebook. Great at churning out drafts, but it still needs your oversight to get it right.

Byte 2: Agentic AI — Giving the Farm “Hands and Feet”

If GenAI is the brainiac of the farm, Agentic AI is the hands and feet. It doesn’t just “think” — it does. It moves hay bales, opens gates, and gets chores done without waiting for you to push every button.

Think Microsoft AI Agents, Salesforce Einstein Copilot Agents, Google Workspace (Gemini-based) agents.

What it can do:

• Chain tasks (research → draft → update CRM → schedule)
• Work toward goals, not just single prompts
• Take initiative like a junior farmhand who knows the routine

Lay definition: Agentic AI gives Generative AI the “doing ability” — or as Marcus Rebelo puts it, “hands and feet.”

Emerging capabilities (not yet fully hands-off):

• An enterprise agent that monitors sales pipeline signals, drafts follow-ups, and books meetings
• A manufacturing agent that predicts equipment issues and could create ERP work orders
• Help desk agents that answer calls, fix certain issues, or route to the right human

⚠️ Still needs human oversight — the cattle don’t manage themselves.

👉 Exec takeaway: Agentic AI turns AI from a note-taker into a true farm worker. Early, but the productivity lift is real.

From the ACA Stage: At our recent ACA event, Marcus Rebelo (Auxiom’s CISO & Head of AI) sat down with Mykolas Rambus (CEO, Hush) to unpack practical agentic workflows with guardrails.

Key points included:

• Privacy-by-default: design workflows so sensitive data never leaves approved systems.
• Accountability: every agent action should be traceable (who/what/when), just like a human teammate.
• Human-in-the-loop (HIL) is important today, but may fade as systems advance.

Byte 3: Artificial General Intelligence (AGI) — The Wildcard Animal

Every farm has that legendary creature people whisper about (think John Dutton). For AI, that’s AGI — the “super-animal” that could think, reason, and create like a human farmer.

Think of AGI as the eventual end-state: flexible, reasoning intelligence that doesn’t exist yet.

What it would mean:

• Mastering any intellectual task humans can
• Reasoning across domains
• Human-level creativity/problem-solving

Reality check:

• Timelines range from 5 to 50 years (some predict breakthroughs as soon as late 2025)
• Raises major ethical/governance questions
• Not relevant for day-to-day planning yet

👉 Exec takeaway: AGI is the mythical stallion of the farm — game-changing if it arrives, but don’t plan this season’s harvest around it.

Byte 4: AI’s Real Costs — Who’s Paying for the Farm?

AI looks magical, but it’s expensive to feed. Providers burn billions on compute (consumer tiers are often subsidized).

Enterprises pay steep licenses and face internal costs:

• Staff training & enablement
• Data cleaning/prep
• Integrations and workflow redesign

Security and Privacy:

• Always know how data is used, shared, or sold.
• Remember: If it’s free, you are the product.
• Frameworks like NIST’s AI Risk Management Framework or ISO/IEC 42001 help set guardrails.

👉 Exec takeaway: ROI comes from integration and adoption, not just licensing. Count the full cost—feed, barns, and farmhands. And never ignore security.

Byte 5: Leadership Still Owns the Barn

AI can draft, summarize, and take some initiative—but it can’t:

• Define visionInstill culture
• Make values-based trade-offs

👉 Exec takeaway: Don’t outsource culture or judgment. Lead with clarity: “Here’s where we use AI, and here’s where we don’t.”

Warning Byte: From the Stage

Marcus and Mykolas also spotlighted the risks we can’t ignore:

AI Supercharging Threats:

• AI-generated phishing emails are 350% more effective than traditional ones
• Deepfakes can now be created with as little as 10 spoken words and 6 photos

Real-World Losses:

• A Hong Kong multinational lost $20M in a deepfake scam
• Another exec avoided loss with a simple follow-up verification step

Defense Strategies:

• Use challenge-response keywords for sensitive transactions
• Enforce multi-factor authentication and layered verification
• Train staff to verify IT requests (fake “IT support” calls are a new ransomware entry point)

Emerging Risks:

• Open-source software vulnerabilities (e.g., Delaney hack)
• Voice cloning + fake emergency calls
• Zero-font/hidden-code exploits bypassing traditional defenses

👉 Action for Leaders: Review password policies, wire transfer checks, and employee training. Even one weak link—human or technical—can be exploited at scale with today’s AI-powered tools.

Bonus Byte: Try This Tomorrow

Pick one time-sink and run it through AI as a quick experiment:

• Ask Copilot to condense yesterday’s 20-email chain into 5 takeaways
• Drop a meeting transcript into Fireflies, Otter AI, or a similar tool and compare to your notes
• Have GenAI draft a client email or proposal; you do the final pass

Why: Small wins show where AI fits your workflow—and give you credibility to guide team adoption.

Engagement:What’s one task you’d hand off to AI tomorrow? Reply and let us know.

Wrap-Up

You don’t need to wait for AGI:  • GenAI is the draft machine  • Agentic AI is the emerging teammate  • AGI is still somewhat theoretical  • Costs matter (external + internal)  • Leaders set the culture and guardrails    Act now—clear-eyed and pragmatic. The leaders who do will reap the harvest; those who wait will watch from the fence.

Sponsor Note

Brought to you by Auxiom — helping executives cut through the noise and apply technology where it actually creates advantage.    P.S. Miss the Marcus Rebelo × Mykolas RambusACA chat? Reply and we’ll send a recap of the key takeaways.

Thank you to our sponsor 🛡️ Auxiom 🙌

This edition was proudly sponsored by Auxiom.

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