This is Precisely When Chatbots Turned Pro
Written by: Jules Flesner
Artificial Intelligence has been around since the 1950s. The leap to modern AI [late 2010s] followed by the release of ChatGPT [2022] has kicked off a historic innovation cycle. Think: life before and after the internet existed.
Here, we’ll focus on one key application of today’s conversational AI technology: customer service chatbots. You usually encounter them on a company’s website or inside a customer portal, but sometimes you’re emailing with them, or even listening to voicemails they've left you, without realizing it.
Old-School Chatbots (1990s–2010s)
Scripted responses: They followed decision trees or pulled from a pre-set answer library.
Limited memory: Bots were… kinda clueless. Each customer question was treated like it was the first time it had ever been asked.
Keyword triggers: If what a customer typed contained the word “hours” the bot might respond with “Our hours are 8 to 6,” but would miss anything outside its script.
Reading between-the-lines: Bots couldn’t “understand” tone, emotion, or cultural/contextual clues within customer questions.
Seen as annoying: Pop-ups were more like FAQ machines, answers that customers probably already found elsewhere on the website. Bots passed customers off quickly, which is annoying, especially if no (trained, happy, helpful human) is available.
Modern AI Chatbots (Late 2010s–Present)
Natural language understanding: Conversational AI bots process full sentences (vs. keywords only).
Context awareness: They can “remember” what was said earlier in the same chat and apply that “knowledge” in later conversation flow.
Machine learning: Bots can get smarter over time by analyzing interactions and adjusting responses.
Integration-ready*: The service powering a modern bot can often connect with CRMs, scheduling tools, payment + debt collection systems, and other software, allowing the bot to handle a wider range of tasks and questions (vs. old-school bots pulling answers from just a Q&A script library.)
Customer insights**: Modern bots capture patterns in questions and customer behavior that businesses can use to solve Ops issues + shape UX design improvements.
Getting closer to human-like: They are learning to mimic tone, adapt language, and manage more complex, sensitive conversations. They still struggle with “understanding” emotion or cultural/contextual clues within customer engagements.
Seen as annoying: (Seriously, can we please collaborate, reimagine and replace this website pop-up thing already?!)
Old chatbots had ‘conversations’ like a ping pong game with amateurs. You were lucky to get a few volleys before the ball flew off the table. Today’s chatbots play like pros, reading your moves and firing back sharper returns over time.
These new ping pong pros AI chatbots are joining traditionally staffed (human) customer service teams across healthcare, multifamily, retail and other industry businesses. The catch is, they're still in the process of being "sharpened", often by far-away product development teams who aren't fully on the pulse of your daily business challenges + realities.
What’s the critical takeaway for B2C company leaders? It’s time to accept that modern, customer-facing AI assistants need the same, sometimes more, oversight than a human employee. First they need onboarded, and then they need continuous “sharpening” that only someone on the inside of your organization can handle. Have you factored that into your staffing, budgets, and business plans?
If you haven't, the next few years in business are going to be even tougher than these last few have been.
You’ve been warned ◡̈
*As of today, this is a gray zone + headache for businesses to manage internally, especially when integrations are among separate, private software firms who cannot speak directly. If you need back-end integration support, I can help. Head over to my Contact page and drop in your details.
**This might be the #1 most overlooked power play for shaping your competitive edge, if your AI tools (EliseAI, BetterBot, etc.) are already in place. Don't have the time or team to translate your data? Let’s collaborate.
Disclaimer: This post is for informational purposes only. Always consult a qualified attorney for compliance related to emerging AI technologies.