Making the Case for Conversational AI Agents When Your Company Already Has "Good Enough" AI
- Ilaria Merizalde
- Mar 19
- 7 min read
Updated: Mar 19
A playbook for team leads who see the gaps and want to do something about them, Sequel to Part 1 "When good enough starts showing its edges"
So, you've started seeing the shortcomings of AI language models. Your company's LLM of choice (ChatGPT, Claude, Copilot, Gemini...) works well enough for a variety of things, but also suffers from pesky flaws like unreliable memory, no connection to your actual business systems, and besides, your workload hasn't decreased much.
(If you haven't read Part 1 yet, start here. It covers how to recognize when your current AI setup is holding you back.)
At this point, you're ready to consider a different approach. Perhaps persuade the leadership that there are other AI solutions worth implementing. But you think their default response will probably be some version of:
"It's working fine. Why change?"
We wrote this article to help you answer that question -- and to help you come up with a sustainable plan for change.
1: Introduce Conversational AI
No need to state "this AI thing isn't working." Because AI isn't "bad"; today's LLMs have lots of potentially useful features.
Yet, the LLM's shortcomings you saw are real. The tool may be feature-rich, but the value that each feature brings to you, right now, is hard to prove.
You would rather use AI for something tailored and specific.
For example, you'd like it to manage lead capture instead of relying on clunky contact forms, or to handle FAQs that take up too much of the team's time. Or perhaps you envision consistent writing output from an AI without having to constantly reprompt.
All of this is conversational AI. Practical, no-fuss, business-savvy AI.
You want to focus on what's possible versus what you're currently getting.
To get buy-in on such a program, you could say:
"Our LLM is a good general-purpose tool. But right now we're only getting answers from it. We could be getting qualified leads, customer insights, and real time savings across multiple teams. A conversational AI agent builder may be right for us."
You're not saying "ChatGPT is bad"; you're proposing a tune up of your company's efforts around AI. You're thinking of what your team and your company can achieve with AI when it's purpose-built and connected with the apps you use every day.
2: Speak Executive Language
Executives tend to focus on the big picture, on tangible outcomes. Land the message by connecting your proposal to the metrics they care about.
Here are some tips by leadership role ~
For the CFO or finance-minded executive:
Every conversation with a nemo agent generates usable data:
Which questions come up most
Where users drop off
Which leads are worth pursuing
Leads get qualified automatically, before a human spends time on them.
Support volume goes down as the agent handles repetitive questions reliably.
For the COO or operations lead:
No-code setup means any team in the company can build agents and make changes without developer help.
Agents integrate with your CRM, cloud storage, and scheduling tools, so they work inside your current systems rather than alongside them.
You get transparency and measurable results, without cumbersome implementation processes.
For the CEO or general manager:
Your company stays in control of its AI. Training data is private, conversations are on-brand, and you can see exactly what the agent is doing and how it's performing.
Companies that use AI to capture intelligence from every customer interaction are set to make better decisions than those that don't (competitive advantage.)
You don't need to make all the arguments at once. Select topics that fit the profile and the priorities at hand.
3: Handle the Custom GPT Question
Someone may ask: "Can't we just build a custom GPT and do basically the same thing?"
It's a fair question. But custom agents and GPTs aren't really the same.
Here's a straightforward comparison~
Custom GPTs:
Only work inside one platform (your customers need an account to use them)
Can't capture user data or generate leads
Don't connect to your CRM or business systems
Limited to one AI model provider
Minimal branding and customization
nemo conversational agents:
Deploy anywhere: your website, WhatsApp, Slack, Facebook, internal portals
Capture contact information and conversation data from every interaction
Connect to your existing systems and workflows
Let you choose the best AI model for each agent's specific job
Fully branded experience that looks and sounds like your company
Private training data that stays protected
To put it briefly, a custom GPT (while a bit more tailored than an LLM as-is) still functions as a personal assistant.
On the other hand, nemo conversational agents are meant to be business tools, which you instruct to handle the repeated yet strategically important conversations that can be automated. And they keep the message on-brand, focused, and human-first.
4: Make the Multi-Model Case
Big-name LLMs dominate the headlines, going up and down with public opinion and new features being launched. Meanwhile, solutions like nemo are getting work done without the drama. It's kind of nice to not tie your company to any one LLM (while still using the best features from each.)
At nemo, we have shown the appeal of multi-model.
nemo gives you a lot of freedom you simply don't have when you sign up your whole company to an LLM or two. And who doesn't like freedom?
Different strokes for different folks... and teams
A customer support group might want a model capable of natural, empathetic conversation. A legal or compliance crew could emphasize careful and precise handling of long documents. A marketing team likely desires creative flexibility.
When your company relies on a single LLM, every group gets the same tool and has to figure out how to adapt it to what they want. That figuring out not only takes time, but becomes a source of internal inconsistency.
With nemo, you can build different agents for different folks, each powered by the AI model best suited to that group. One platform, multiple specialized agents. Nobody gets stuck with a tool that's "fine for everyone, perfect for no one."
That's a compelling argument for leadership: focus on efficiency and fit, instead of simply "trying to keep up" with technology.
5: What Disruption? It's Just a Pilot.
A common roadblock on the way to positive change is fear of disruption.
This is usually when one or more of the stakeholders starts hitting on the brakes of an otherwise great idea. <<-- Must avoid.
Know this:
nemo isn't made to disrupt. We don't want you to blow everything up and start over* (nemo, unlike other AIs, it keeps humans not only in the loop, but at the center.)
At nemo, we embrace incremental change.
Got change-resistant executives? Avoid things like:
NO company-wide rollout
NO large budget
NO ambitious 12-month roadmap
-->>Instead, propose something small, focused, and measurable.
Work to structure your proposal like this:
Pick one use case, something with clear, repetitive volume. Customer FAQs and inbound lead qualification are proven starting points because the impact is visible quickly.
Define success metrics upfront. Response time, leads captured, questions resolved without human intervention, hours saved per week. Agree on what "working" looks like before you start.
Set a short timeline, like four to six weeks, then measure results. Enough time to gather meaningful data; not so long that it doesn't seem like a commitment.
Keep the team lean. One or two people building and managing the agent. No new hires, no retraining, no pulling people off other projects.
Run it alongside your current setup. Your existing tools stay in place while you test -- and you can compare the same task on nemo and your existing LLM.
Show what becomes possible when you move from general-purpose answers to purpose-built agents, and to do it with real data from your own business.
*Plus, you may still need a big-name LLM for things like image generation. But business conversations? Definitely give nemo a spin.
6: Leap Forward, Data in Hand
Once your pilot delivers results, you're off to the races. That's what any change-resistant exec can no longer resist: cold, hard facts.
At that point, your next meetings can focus on building momentum.
The customer FAQ agent proved its value. Now let's build a lead qualification agent for the sales team.
The sales agent is capturing data we never had before. Let's add an internal knowledge agent for onboarding new hires.
Each new agent builds on what you've already learned. The platform is the same. The process is familiar. The cost of expansion is low.
In other words, with minimal effort, your pilot showed what's really possible for your particular situation and company. It's diametrically different from the usual approach to new technologies: Wow, look at this amazing tool! Let's figure out how it can work for us.
A nemo pilot gives you steady, measurable progress toward tangible business outcomes. Think of all the uses for nemo conversational agents - agents which you comprehensively train and who reference exclusively the materials you provide, dutifully representing (and building) your brand 24/7.
Going from "Good-Enough" to "Real-Good" AI
Your company is already using AI in some form. The next step is figuring out how to harness its power to manage and optimize business conversations.
And it involves a process of persuasion, a negotiation between forward-thinkers and those who think twice (or more).
A big-name LLM free or paid account doesn't connect to your systems, writes with mixed-up references, and provides no systematic conversation capture. It's a tool for anyone and everyone -- without a clear way forward specifically for you, while:
A purpose-built nemo conversational agent is trained for a specific job, connected to the tools your team already uses, deployed where your customers actually are, and generating useful data with every interaction.
You just need one good pilot and the numbers it produces.
So, if you want to go from "good enough" to "real good", give nemo a try.
What conversations could you be having with clients and prospects? When are clients not being helped quickly enough? Where are the gaps that a conversational agent could fill?
If you're ready to start answering these questions with a nemo agent, get started with nemo today.
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