In this episode of Voices Beyond Borders with Emma Woelk, we dive deep into the real mechanics of AI adoption inside companies — far away from buzzwords, hype, and PowerPoint visions.

My guest, Driss Farissi, founder of H-IN-Q, has spent more than 20 years in global market research and AI-driven process automation.

He explains how companies can unify feedback from all channels — WhatsApp, email, chat, phone, and social — and build a single data layer that turns scattered signals into immediate, actionable decisions.

We discuss why most digital transformation projects fail long before the tech is ready, how to overcome internal resistance, and why the smartest companies start with small pilots instead of massive roadmaps.

You’ll also learn how speech-to-text, computer vision, and automated sentiment tracking create real-time visibility for Sales, Customer Success and operational teams.

If you want to understand how to implement AI systems that actually get adopted — not just bought — this conversation gives you the pragmatic blueprint.

00:00 Intro — Why customer signals are the real foundation of AI

02:45 Driss’ background and the move from research to AI systems

08:10 How to unify WhatsApp, email, chat and social into one feedback layer

13:20 Speech-to-text, computer vision and automated analysis

18:40 Why AI projects fail: resistance, culture, and missing involvement

25:05 Starting small: low-hanging fruits and ROI-first pilots

32:10 Real-world cases: what worked and what failed

38:55 The vision: building a Single Source of Truth across the company

45:20 Final takeaways & the automation roadmap

What You’ll Learn

– How companies transform scattered customer inputs into real-time decisions

– Why a Single Source of Truth is the backbone of every AI initiative

– How speech-to-text and computer vision convert natural feedback into structured data

– How to detect early-warning signals and trend shifts automatically

– Why adoption fails when teams aren’t involved early

– How to design AI pilots that deliver ROI in days, not months

– The best starting points for automation in mid-sized organizations

– Why data culture matters more than tools or model selection

Key Discussion Topics

1 — Building a Real “Single Source of Truth”

How to consolidate WhatsApp messages, emails, chat conversations, social posts and support interactions into one data layer.

Why this matters for Sales, CS, operations and leadership — and how it enables faster, more accurate decisions.

2 — Speech-to-Text & Computer Vision in Business

How natural language and image input become structured insights using speech-to-text pipelines and visual classifiers.

Real use cases where teams shorten manual work from hours to seconds.

3 — Adoption, Resistance & Team Involvement

Why employees resist digital projects even when the tech works.

How to involve teams early, create ownership and avoid silent blockers that kill automation.

4 — AI Pilots That Deliver Fast ROI

Why starting small creates momentum.

How low-hanging-fruit automations outperform big “AI strategies” — and how to prioritize correctly.

5 — Detecting Signals Before They Become Problems

How automated feedback systems reveal trends, sentiment shifts and anomalies weeks before traditional reporting would notice.

Why this matters for churn prevention, quality control and retention.

6 — The Vision: A Unified Decision Layer

How AI-enabled companies move from manual processing to real-time insight loops.

Why this becomes the operating system for the next decade of business.

Actionable Insights

– Identify 3 customer signal sources you’re currently not analyzing

– Build a micro-pilot: unify one channel (e.g., WhatsApp) with basic speech-to-text

– Add real-time flags for churn risk or customer dissatisfaction

– Involve the team early and ask: “What slows you down weekly?”

– Prioritize automations that remove repetitive work first

– Define a long-term vision, but deliver in weekly steps

– Track response time, sentiment trends and anomaly spikes as new KPIs