The Implement AI Podcast #59 – How to Actually Build an AI-First Business

May 6, 2025
AI-first

Artificial Intelligence (AI) is moving beyond the hype cycle to become a deployable force reshaping modern business operations. While flashy demos capture attention, the real challenge lies in effective implementation. How can organisations strategically build an AI-first foundation?

In episode 59 of The Implement AI Podcast, Piers Linney and Dr. Aalok Y. Shukla address this critical question. Drawing from extensive experience with SMEs and large enterprises, they outline the essential building blocks for creating an AI-augmented company, focusing on actionable strategy.

Here’s what you need to know if you’re serious about integrating AI into your operations.

Why AI Implementation Often Fails

Piers and Aalok kick things off by identifying a common trap: businesses getting lost in AI hype without real deployment strategies. Many try to adopt siloed AI tools, like email responders here and analytics assistants there, without a centralised system or scalable architecture.

The problem? Disconnected vertical AI agents may solve specific problems but rarely create sustainable impact across the business.

Instead, Aalok highlights the need for a holistic, horizontal AI operating system (AIOS), a centralised platform that integrates AI agents across key functions like sales, customer service, support, and operations. This ensures AI doesn’t just live in pockets but becomes woven into the organisational fabric.

The 3 Core Components of an AI-First Business

The Implement AI team has distilled their learning into a three-part blueprint:

  • Configurable AI Agent Teams
    Instead of treating AI as one-off tools, businesses need digital teams. These AI agents collaborate, pass tasks between each other, and automate processes just like human teams do. One agent might gather data, another validates it, while a third acts on it.
    Whether you’re in retail, legal, logistics, or even healthcare, these digital teams can be tailored to your domain, automating everything from customer follow-ups to compliance documentation.
  • Agentic CRM
    Aalok introduces a revolutionary upgrade to the traditional CRM: an AI-native system that captures and analyses structured and unstructured data across all communication channels: email, WhatsApp, SMS, calls, etc.
    Unlike legacy CRMs that bury valuable insights in unreadable notes, the agentic CRM stores data in an agent-friendly way. That means your AI workers can detect sales opportunities from past calls, identify churn signals, and even enrich customer profiles with third-party data, without human input.
  • Agentic Task Engine
    The glue that binds everything together, this engine acts on triggers to execute complex workflows. Imagine this: a customer says, “Call me in six months.” The system logs it, schedules the call, and reminds your agent. Or maybe your competitor launches a new product, your AI detects it and updates your strategy dashboard. This is how businesses start to act on data in real time, not after the fact.

Why Centralisation Matters

Experimentation alone isn’t enough anymore. While pilot programmes are useful, many companies get stuck there. The businesses that win will be those that can scale AI across departments.

That’s why Piers and Aalok advocate for an AI Operating System, an internal digital infrastructure where new agents can be deployed rapidly, monitored, upgraded, and scaled. This eliminates the chaos of juggling 20 different AI vendors for 20 different needs.

With AIOS, businesses build an internal framework where AI is no longer an add-on but a core part of their DNA.

Humans in the Loop

One fear many businesses have: Will AI take over everything?

The answer from Implement AI is clear: NO. AI should augment, not replace. Their approach is “human in the loop,” meaning AI handles the grunt work so people can focus on higher-value tasks.

They’re not just shipping AI software; they’re building managed AI agents. These are pre-trained, fully supported digital workers that businesses can deploy, like hiring a new employee. Implement AI helps with onboarding, training, and ongoing updates, just like a good IT or HR department would for people.

Real-World Applications

Let’s see some practical examples:

  • Sales: AI agents sift through customer data, find warm leads, and trigger outreach.
  • Customer Support: Automated follow-ups, knowledge base lookups, and ticket escalation.
  • Compliance: AI tracks what was promised to clients, making audits and reviews seamless.
  • Analytics: Daily insight reports highlighting missed sales, customer churn risk, or upsell opportunities.

All of this without overwhelming the team because each department plugs into a central AOS.

Final Thoughts

Becoming an AI-first business isn’t about installing the latest tool; it’s about rethinking how work gets done. It’s about centralising AI efforts so every department benefits. It’s about building configurable teams that grow with your business. It’s about maintaining human oversight while letting AI handle the rest. And ultimately, it’s about creating an organisation that can act on more data, faster, and more intelligently than the competition.

Also, keep an eye on the upcoming “Your Future Digital Workforce” event in London, on the 20th of June, as we’ll discuss:

  • The state of AI agents today
  • What a digital workforce really looks like
  • How to go live with AI agents

This is a behind-the-scenes perspective on how AI agents are transforming the workplace and what leaders need to do now to remain competitive.

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