The Digital Executive Podcast – Episode 1033

AI-Powered Business Optimization: The Future of Decision-Making with CEO Avrom Gilbert
Date: March 25, 2025

Guest: Avrom Gilbert, CEO of SparkBeyond
Host: Coruzant Technologies

Episode Overview

This episode centers on how artificial intelligence—especially generative AI (GenAI) and agentic AI—is reshaping business decision-making and operations at scale. Host Coruzant Technologies is joined by Avrom Gilbert, CEO of SparkBeyond, to discuss:

• The evolution of AI in high-growth companies,
• The next transformative leaps for AI-driven business optimization,
• The rise of agentic AI as an industry force,
• Real-world use cases for “always optimized” AI-powered businesses.

Avrom draws vivid analogies, references real clients, and brings decades of experience to illuminate practical and futuristic possibilities with AI.

Key Discussion Points and Insights

1. The Evolution of AI in Business Decision-Making

Timestamps: 01:39 – 05:29

• Era Breakdown:
  • Pre GenAI: AI was present but not widely accessible. Tools available to select enterprises (e.g., SparkBeyond’s pioneering offerings) focused on analyzing structured data (CRM, ERP, IoT) to improve KPIs.
  • Post GenAI: Catalyzed by ChatGPT, AI became much more accessible and powerful. Decision support is now rapid, data-driven, and can compress weeks of research into seconds.

“There’s really two periods of time...the pre gen AI and the post gen AI.”
—Avrom Gilbert (01:39)

• Agents in Decision-Making:

  • The next wave is agents (AIs) making decisions—handling everything from trivial daily choices (“what to cook for dinner”) to significant operational issues (customer service, maintenance).
  • Trust in agents is growing; expect mass adoption soon.

• The “Jarvis” Analogy:

  • Gilbert likens the future of AI to “Jarvis” from Iron Man, able to deeply understand and optimize every business operation.

“Maybe we’ll be able to have an AI which we can ask questions like how do I reduce the cost of my business?...That’s an AI I can trust.”
—Avrom Gilbert (04:18)

• The Main Hurdle:
  • Current LLMs (Large Language Models) have “world knowledge” but lack business-specific insights. The real secrets for KPIs live in proprietary operational data, not public internet sources.

2. The Next Big Leap in AI-Driven Optimization

Timestamps: 06:07 – 07:17

• Deep Contextual AI:
  • True value emerges when AI has real-time, granular understanding of unique business operations.
  • Example: AI predicts machine failures in factories using sensor data and triggers proactive maintenance. Or, it discerns micro-segments of customers with tailored promotions to maximize revenue.

“That LLM having not just world knowledge, but actually the capabilities and understanding of what drives the real world and specifically my business, that’s going to be a big deal.”
—Avrom Gilbert (06:36)

• Mass Scalability:
  • AI can manage thousands of micro segments, tailoring and sending millions of messages autonomously—a game changer in scale and efficiency.

3. The Rise of Agentic AI

Timestamps: 07:44 – 10:02

• Why Now?:

  • LLM quality is improving rapidly, with shockingly advanced capabilities.
  • The technical barrier is dropping—anyone can soon create an agent via simple language instructions.

• App Store Analogy:

  • Agentic AI is likened to the explosion of mobile apps after the App Store launched.
  • Pre-app era: building apps for phones was tough and exclusive.
  • Post-App Store: creating and sharing apps became mainstream, leading to over a million apps in just a few years.
  • Expect a similar proliferation of AI agents solving niche and mainstream problems.

“What we should expect is just a multitude of AI agents...the barriers to building agents are getting lower and lower.”
—Avrom Gilbert (09:29)

4. Real-World Example: “Always Optimized” AI at Work

Timestamps: 10:30 – 13:18

• The Old Way:
  • Manual, slow, and siloed: Data scientists analyze customer churn only when they have time; findings trickle to marketing; marketing executes interventions—delayed and expensive.
  • Avrom quotes Winston Churchill: “Democracy is the worst form of government, except for all other types...This is a terrible way to optimize your business, but without AI, it’s actually the best...”

“It’s how Churchill used to describe democracy...This is a terrible way to optimize your business, but without AI, it’s actually the best and most practical way.”
—Avrom Gilbert (11:28)

• "Always Optimized" AI Cycle:
  • AI constantly monitors, micro-segments customers in real time, identifies problems, and triggers interventions (like custom emails to win back customers).
  • Approvals by humans can be retained, but AI is ready to execute autonomously once trusted.
  • Applications extend across fraud detection, cost analysis, energy optimization, and more.

“Always optimized means that AI does the hard work...we figured out the way to educate an LLM how to become an expert in the relevant parts of your business.”
—Avrom Gilbert (12:39)

Notable Quotes

• On AI’s Evolution:
  “There’s really two periods of time...the pre gen AI and the post gen AI.”
  —Avrom Gilbert (01:39)

• The Jarvis Vision:
  “That’s an AI I can trust with achieving my business goals or to make decisions for me.”
  —Avrom Gilbert (04:18)

• Transformational Impact:
  “That LLM having...the understanding of what drives the real world and specifically my business, that’s going to be a big deal.”
  —Avrom Gilbert (06:36)

• On the Proliferation of AI Agents:
  “What we should expect is just a multitude of AI agents...the barriers to building agents are getting lower and lower.”
  —Avrom Gilbert (09:29)

• Old vs. New Optimization:
  “This is a terrible way to optimize your business, but without AI, it’s actually the best and most practical way.”
  —Avrom Gilbert (11:28)

• On Future Normalcy:
  “Always optimized capability is going to be perfectly natural for organizations in the coming years as we grow to trust LLMs and generative AI much more.”
  —Avrom Gilbert (13:13)

Memorable & Engaging Moments

• The Iron Man “Jarvis” analogy (04:00–05:29) vividly paints the immersive, trustworthy AI assistant soon within reach.
• The rapid shift in application/agent development compared to the “App Store moment” (08:20–10:02).
• Churchill’s democracy quote humorously sets up the inefficiencies of traditional business optimization (11:28).

Key Segment Timestamps

• 01:39–05:29 – Evolution of AI in decision-making, “Jarvis” analogy
• 06:07–07:17 – Next leap: deeply contextual, business-aware AI
• 07:44–10:02 – Momentum of agentic AI; app store analogy
• 10:30–13:18 – Real-world example: “always optimized” AI in action

Closing

Avrom Gilbert foresees a near future where businesses rely on “always optimized” AI that intimately understands—and autonomously acts upon—their unique operational realities. The barriers to deploying such transformational agents are falling fast, and the analogies to “Jarvis” and the App Store help make this future both tangible and inevitable for listeners.