What Questions Should You Have?
Bland has grown exponentially over the past year. With this growth, comes new use cases and new customers.
We’ve sat through many implementations from ideation and concept to production launches. In the early phases we started to notice that once the project involved those at the director and executive levels of the organizations the same few questions always come up. Some of them are routine and expected, but a few surprised us.
This article covers all of the key and common questions we go through.
Brief Intro to AI Phone Agents
If you’re new to AI phone agents and how they operate, it’s worth reading our beginning material here.
Executive Priorities With Phone Agents
Leading a department or entire organization comes with a significant amount of responsibility. Beyond hitting more fundamental metrics each quarter, an executive is also responsible for managing risk and improving internal function. All priorities can be broken down into three major buckets.
Cost Leading
Sell more, spend less. The quintessential equation for managers is to keep their costs in check while getting their product or service in the hands of more customers.
Production Enhancing
Can service be improved? Product quality increased? Customer satisfaction bolstered? All process and product related priorities are all about doing things better.
One of the biggest factors in increasing the likelihood of a sale is how long it takes to call a prospect back. One of the easiest ways to sour your customer service ratings are to keep people on hold and make them repeat their questions to multiple operators.
AI phone agents address all of the major issues and inconsistencies with phone operator quality in a completely revolutionary way.
Call centers are a notorious pain point when it comes to customer satisfaction. So are large scale outbound calling and sales teams. Many enterprises are faced with two hard choices, either building and managing their own call operator networks or outsourcing to specialist firms.
Neither option has been shown to improve either quality or costs of calls, but enterprises have had no alternative until the rise of sophisticated AI phone agent systems.
Risk Reducing
This is an ever-present priority that varies wildly based on the specific industry. How can risk to the company and its customers be reduced with every initiative? In some industries this is a simple manner. In others like finance or healthcare it’s a far bigger concern.
Risk controls in regards to phone agents are tightly managed by Bland for every enterprise customer. They use hard-controls, or ‘guard rails’ that are optimized per specific use case to mitigate the risk of any compromising speech by an AI agent.
Furthermore, Bland’s robust logging and real-time monitoring capabilities of all phone agent calls provides a sophisticated way to manage quality control of phone calls. A well designed monitoring system will fit perfectly into an enterprise level quality assurance operating procedure.
It’s with these three major categories in mind that we are fielding questions from business and industry leaders.
How Reliable Are AI Phone Agents?
There are two factors when it comes to reliability that are discussed when evaluating AI phone agents. The first is technical reliability, meaning how many callers can be handled at the same time? Do calls ever get dropped due to bad hardware performance, or busy lines?
Providers like Bland have scalable, redundant infrastructure spread across the globe that’s vetted and verified by the largest cloud providers.
The second factor of reliability is in experience. How well do AI agents perform? Can they do the job of equal or better those that they are replacing (call center operators)? The latest generation of AI phone agents sound and speak like people, not robots. They can interpret speech, think, and respond in real time to the person on the other end of the line.
How about when it comes to reliability in service? Are the agents capable of handling the wide variety of caller inquiries, questions and complaints? In short, yes. But this is where the quality of your implementation team will come into place (not all agents are build equal).
How Scalable are AI Phone Agents?
The question of scalability comes up in early discussions often. How many calls can be supported at a time? What kinds of daily call volume is possible?
Thanks to Bland.ai’s new globally built infrastructure, there aren’t many limits on enterprise scalable implementations of AI phone agents. There has not been an enterprise implementation yet that has seen performance issues at scale.
What Resources Do I Need to Build Enterprise Level AI Phone Agents?
Let’s talk about internal teams, and implementation. The beauty of AI Phone agents (and the tools that Bland has built to construct them) is that their complexity can grow to meet your use case needs. A small business that needs to field reservations and inquiries can build their AI phone agent with a single motivated technical person. Trying to replace an entire lead qualification sales team? That’s a much more involved build.
The best way to truly gain insight into the resources required would be to get on a call with a Bland team member and explain your use case in detail. At this point, the team has been involved with every kind of use case imaginable.
Are AI Phone Agents Secure? What happens to my customer’s information?
Bland holds both SOC-II Type 1 and Type 2 compliance certifications. In addition, all systems are fully HIPPA compliant. In shorter terms, your customer data and all call data is stored on state of the art, encrypted databases and secured in transit. Access to call data and platforms follow all standard regulations. For more information on Bland’s robust compliance, please reach out to our enterprise team.
What Are the Risks
It’s no surprise that a new company considering an AI powered call center solution would be wary of unleashing automated agents on real live customers and prospects. How can you guarantee that things your AI agents say won’t create liabilities, or potential lawsuits?
These are valid risks, and well documented and discussed in the artificial intelligence community. Fortunately, in the context of phone agents risk mitigation is not only possible but the default in a platform like Bland’s.
Building Your AI Phone Agent Implementation Plan
As you may have guessed, not every possible permutation and question can be answered for your company and use case in a blog post. But we hope that this post provided a nice overview of the main components of any well thought through AI agent implementation strategy. Well designed AI agent systems can lower costs, improve reliability (at scale), and even reduce and manage risk in any given application.
