“No way! Our business is not Google or Amazon, and we don’t have the same budgets. Besides, our company doesn’t even have programmers”. This is roughly what some entrepreneurs think when it comes to implementing AI. All of this is the result of misconceptions that cause businesses to miss out on profits. AI is already changing the business world and those who don’t adapt risk being left behind. Here are common myths about AI and tell you why they’re not true.
- Myth 1: AI is only necessary for large companies with complex processes
- Myth 2. It's expensive
- Myth 3. AI is incapable of taking into account the nuances and peculiarities of business — unlike humans
- Myth 4: Special knowledge is required to customize and use AI
- Myth 5. Implementing AI takes a long time
- Lastly: what to keep in mind if you are in doubt about whether to connect AI
Myth 1: AI is only necessary for large companies with complex processes
Well, what SME tasks can artificial intelligence perform? We have everything standard, but a human can cope with it. A completely different matter is large companies with ambitious goals that can invest a lot of money in innovations. For example, to develop solutions that make predictions based on thousands of parameters. And, in general, training artificial intelligence requires large amounts of data — and we simply do not have them.
Why it’s not true
Although large businesses started implementing AI, small and medium-sized businesses are already getting more involved in the process. In 2021, only 6% of small businesses in the EU and 13% of medium-sized businesses used AI technologies. Now, 14% in Germany, a rather conservative country, admit that they are increasingly using AI.
SMBs are using AI in different areas: e-commerce, healthcare, insurance, and manufacturing. AI is used for customer service, forecasting and automating business processes.
That said, digital assistants can be even more useful for smaller companies. They can help relieve the workload of employees who, in small businesses, already have to combine several roles at once. Here are a few examples:
- generating creative ideas without distracting the team with brainstorming;
- replacing first-line operators — i.e., counselors who answer basic customer responses;
- developing design or text at the user’s request;
- fast, error-free calculations.
At the same time, artificial intelligence does not necessarily have to be trained on its own data. For example, language analytics services already have a sufficient amount of data, so AI can be immediately used for your business.
Myth 2. It’s expensive
Developing AI systems can be very expensive. You must hire highly qualified specialists, buy powerful equipment and license software. Such investments are unaffordable for many companies, especially small and medium-sized ones.
And then there is more: when AI is developed and implemented, it will need to be constantly maintained and updated, which is also an additional expense.
Why is this not true
All of the above is only true for situations where you are developing artificial intelligence from scratch. In reality, not many companies choose this path. There are many ready-made solutions where development and support are entirely on the platform. And the user only has to pay and follow updates. In addition, some aspects of AI become even cheaper over time:
In addition, in business, it is inappropriate to say that something is too expensive. You have to start with whether the introduction of AI pays off. And the experience of many companies proves that the introduction of artificial intelligence is quite cost-effective:
- a joint Microsoft and IDC study found that for every $1 invested in AI, the return on investment is $3.50, with an average ROI of just 14 months;
- an Autonomous Research report found that AI could reduce operating costs for financial firms by 22% — which could amount to $1 trillion in savings by 2030;
- Capgemini found that 75% of AI-enabled financial institutions experienced a 10-20% reduction in fraud, correspondingly reducing under-recovery.
Myth 3. AI is incapable of taking into account the nuances and peculiarities of business — unlike humans
AI may have large amounts of data, but it doesn’t have the same life experience and knowledge of the industry’s intricacies as a human. Every company is different, and you’re proposing an algorithm that works the same for everyone?
At the end of the day, no one compares to an expert who has been with a company for years and knows its processes well from the inside. Yes, he or she may be unproductive, subjective, or distracted at times. But what can you do? The algorithm will not be as well versed in the peculiarities of a particular company anyway.
Why is this not true
Artificial intelligence is quite capable of taking into account the peculiarities and nuances of business. This is the principle behind our Ringostat AI Supervisor service, which allows you to monitor 100% of conversations with customers. As part of this service, we study a company’s processes in detail and digitize the experience of its supervisor — that is, the person who usually analyzes call handling or online meetings.
To do this, the business:
- gives us scripts of conversations, internal rules or instructions;
- shows us what stages customer conversations are usually divided into and what actions managers are required to take at each stage;
- agrees on what score the manager receives for each action.
Once the artificial intelligence is customized, the business gets a digital assistant that takes into account smaller nuances. Like a person who has been with the company for a long time. Let’s take a brief look at how it works.
- After the conversation, the solution transcribes the audio conversation into text. AI understands over 50 languages and can translate the dialog if needed.
- Captures a summary of the conversation, so you don’t have to listen to or read the entire dialog.
- Gives advice on the manager’s next steps, such as sending documents or arranging a visit to the client.
- Evaluates the employee’s work by substituting the necessary evaluation criteria. Suppose a company sells 10 products, and there is a separate conversation script for each case. AI understands from the context of the dialog what evaluation criteria to substitute for each stage of the conversation.
- It compiles a portrait of the client, “pulling” information from the replicas that is important for selling a particular business, such as the size of the company, the client’s age, previous experience, etc. This data can then be conveniently copied into a customer card in CRM.
- Captures the mood of the customer, the manager and the overall mood. In this way, management can immediately pay attention to dialogs that need attention. Suppose if customers are dissatisfied or employees are impolite and apathetic.
- Summarizes the main points of the conversation that are essential specifically to your company. For example, whether there was an invoice or video appointment, which rate the customer chose, etc.
Thus, Ringostat AI Supervisor evaluates the processing of requests, taking into account the peculiarities of a particular business. At the same time, he saves a lot of time on control. After all, unlike a human, he does not need to spend time listening to calls, recording the meaning of the conversation and providing feedback to the team.
A clear example of the work of such artificial intelligence is described in “Case: How Ringostat AI Supervisor quickly analyzes conversations according to three scenarios and 90+ criteria”.
Myth 4: Special knowledge is required to customize and use AI
There is no way to do without a programmer for such advanced technologies. Moreover, he must have experience working with artificial intelligence. You will probably have to prepare complex TORs and deal with obscure terms. And what will the results of his work look like, and who will deal with them? Here we will definitely need an experienced additional person on staff who will work exclusively with AI.
Why is this not true
Artificial Intelligence services for business are not that difficult to set up at all. For example, to implement AI from Ringostat, you don’t need a programmer or technical knowledge at all. It is enough to tell what result you want to get and share the scripts of conversations and your company’s rules.
Yes, it would be nice to have a TOR, but even that is optional. The example below is a snippet of the TOR, which simply describes the stages of a standard conversation with customers. As you can see, there is nothing technical here:
If you’re using speech analytics, you don’t need this either. All AI data can be easily interpreted right in your personal Ringostat account. Everything is absolutely clear: what the conversation was about, what the interlocutors’ mood was, what to improve before the next dialog, and so on.
Myth 5. Implementing AI takes a long time
Well, let’s say AI platforms take over the implementation and customization of the solution. But that’s probably quite a long time. At least several months, maybe even more. So businesses can’t count on a quick return on investment. And then the company also have to teach the team how to work with the new tool.
Why is this not true
You can start working with off-the-shelf solutions almost immediately. Turnkey artificial intelligence training is usually longer — but also not critical.
When it comes to Ringostat AI Supervisor, the more information you have, the faster the implementation will happen. Even the presence of conversation scripts will already be enough for our experts to quickly customize the solution for you. The proof is a testimonial from one of our clients.
Lastly: what to keep in mind if you are in doubt about whether to connect AI
- Artificial Intelligence is not a magic wand that will instantly increase your team’s productivity or business profits. As with any tool, you need to work with it constantly, analyze data and implement changes. Human intervention will still be necessary — but it will take much less time.
- If AI needs to be customized for a specific company — prepare to get involved as well. No matter how much you pay a contractor, they can’t learn the nuances of the business or its processes instead of you. The more information you provide — the more accurate the AI will be.
- As your business scales and changes, AI will need to change as well. That’s why it’s better to choose platforms with flexible settings and fast tech support. If you work with little-known and cheaper solutions, there is always a risk that they will “stop developing” and will not be able to meet all your needs over time.
