From hype to help: What real-world AI looks like in 2025 (and how to start)
13 June 2025
Everyone's talking about AI. But who's actually using it to solve real business problems?
That’s the question we explored in our latest Product Pulse webinar, “From Idea to Impact: Real-World AI for Business”, hosted by John Radford (Client Services Director, LogiNet) and joined by two practical AI experts: Martin Gallardo, fractional COO and startup strategist, and Balint Horvath, AI Strategist and Product Expert at Cognitive Calls.
Let’s get one thing clear: AI isn’t just for Silicon Valley anymore. It’s not just shiny demos, fluffy decks, or one-off pilots. It's working quietly, practically, inside businesses that are bold enough to rethink old processes.
Here's what we learned.
Think you need an AI strategy? You don't.
Let’s start with a counterintuitive truth from Martin:
“You don’t need an AI strategy. You need a strategy.”
What he means is this: don’t chase AI for the sake of AI. Start with the business problem. What are you trying to solve? Where do you want to go in 3–5 years? Are you a VC-backed scale-up chasing rapid growth or a margin-driven SME focused on staying lean?
Your AI direction should come from that. Everything else: tooling, LLMs, infrastructure is secondary.
Internal workflows are the secret sauce
Poll results from the webinar showed it: most companies want to start with internal workflows, not customer-facing features.
Balint explained why.
Let’s say you’ve got a knowledge base. Right now, your team is clicking through folders or pinging each other in Slack to find answers. But imagine if they could just… ask. In plain language.
That’s where internal chatbots and AI-powered assistants come in.
They sit on top of your internal documentation and free up time for your most valuable asset: your people.
One example? At LogiNet, our own AI agent Cognitive Calls integrates directly with CRM and ERP systems. It understands real-time context, speaks fluently in multiple languages, and actually books appointments or resolves requests without ever bothering a human, unless it really needs to.
AI isn’t magic. It’s just well-designed software
Here’s something Balint stressed and it often gets lost in the hype:
“Most AI projects are 80% regular software development.”
AI is just another component in the software toolkit. If you don’t already have clean workflows, structured data, or maintainable systems, no amount of AI will save you.
That’s why every successful AI implementation at LogiNet starts with a discovery phase. We map your operations, identify the "boring, repetitive, manual" stuff (because that’s where AI thrives), and design small, measurable projects that deliver value in weeks, not years.
Want ROI? Start with customer support or sales ops
Martin brought in a classic case:
10,000 customer service tickets per month. That’s a nightmare. But instead of hiring more agents, the company layered AI in stages:
- Created solution articles (cutting tickets in half)
- Deployed a text-based AI chatbot in Arabic
- Added an auto-responder that drafts human-like replies to incoming emails
- (Next up) Voice-based AI agents like Cognitive Calls to handle real-time conversations
And it's not just support. AI can massively improve lead qualification, sales follow-up, and even pricing predictions—if you know what data to use, and how to feed it into your system.
“Is AI going to take jobs?” The real answer
The elephant in the room: What happens to people when AI takes over repetitive work?
Martin’s take was refreshingly honest:
“Yes, you’ll automate 80% of some jobs. But don’t just fire those people. Retrain them. Move them to customer success, upselling, or automation roles.”
Balint added:
“Our goal isn’t to replace people. It’s to give them back their time and remove the dull, repetitive parts of their day.”
That’s how forward-thinking companies win. They don’t use AI to cut headcount, they use it to upgrade roles and unlock revenue that was sitting dormant in support tickets, delayed SLAs, or stale leads.
Can you afford to wait?
Here’s the hard truth: you can’t afford not to do AI.
Whether you’re a logistics company fielding inbound quote requests, or a SaaS firm drowning in unqualified leads, the opportunity cost of inaction is real.
Even a basic AI workflow—like enriching a customer form with company data automatically—can signal purchase readiness, detect budget, or route leads smarter. All without touching your dev team.
Martin said it best:
“The winners are the ones who figure out what to do with the freed-up human capacity.”
Final takeaways: Where to start
If you’re not sure how to begin, follow the model we use at LogiNet:
- Don’t start with tools. Start with goals.
- Run an AI discovery session: map use cases, evaluate processes, define success metrics.
- Start small, iterate fast: 90-day sprints with clear value metrics work best.
- Bring business and tech people together in the same room – always.
- Don’t expect perfection. Expect progress. Even if your AI voice bot doesn’t sound perfectly human, if it handles 1000 calls in an hour and updates your CRM, it’s doing its job.
Want the full conversation?
Curious about the full story behind these insights? You can rewatch the entire webinar recording, “From Idea to Impact: Real-World AI for Business,” on YouTube.
Grab a coffee, sit back, and hear directly from our speakers as they share stories, frameworks, and hard-earned lessons about making AI actually work inside organisations.
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John Radford
Client Services Director UK
Providing end‒to‒end web and mobile development services to our customers since 2008.