With Artificial intelligence and its many applications on the rise, multiple sectors are jumping on the AI bandwagon. Many startups are seeing AI as an opportunity, but are not fully aware of the true potential, possible applications, or the challenges they may face. So, what does AI mean for startups? And what do you need to know beyond the buzzwords?
There are Both Opportunities and Threats
Artificial intelligence represents a broad spectrum of opportunities and threats to startups. The opportunities include using available powerful tools to accomplish many business functions, for example. Among the threats is the difficulty in predicting how a startup’s competitors might use powerful artificial intelligence tools to attack their market positions.
So, what does AI mean for startups?
It means that there are many factors to consider, such as infrastructure capacity and potential ethical and regulatory considerations.
There are Infrastructure Requirements to Consider
The companies that take advantage of the most powerful AI tools will need potent cloud and computing capabilities as well as access to enormous amounts of data. This requirement alone favors larger corporations. While this aspect is a challenge for startups, it also represents an opportunity for those companies that can provide the computing power required to harness these capabilities.
For instance, one of the companies I am helping, HotWright, Inc., is developing a computer that will allow for much more flexible management of computing power, and memory requirements. It will also be reprogrammable on the fly. Their Hotstate processor stands out for its small size, fast operation, energy efficiency, and adaptability. This makes it suitable for modern, power-sensitive, and space-constrained applications.
It is especially suited for processing the large language models that underpin many artificial intelligence tools.
A Note on Large Language Models
Since many of today’s AI systems use a large language model, the reader might want to know what that means. The most straightforward description is that a large language model can analyze groupings of words to predict the next word in the grouping. This capability allows applications like ChatGPT to answer questions and perform some tasks in a manner that makes it difficult to distinguish the results from human effort.
How These Large Language Models Work
Large language models (LLMs) use a vector with 12,288 values to represent each word to over-simplify. These 12,288 vector entries then capture the word’s relationship to other words. This vector approach allows the model to analyze a word cluster and determine which word will likely come next. For example, presented with the word cluster, “what word is likely to come ______,” an LLM would use the word vectors to calculate that the word closest to the cluster is “next.”
If you want to understand large language models in depth, here is a very readable explanation that describes the above-referenced vector approach.
What Does AI Mean For Startups? Regulatory and Ethical Considerations Can Create Uncertainty
It’s important to be aware of the potential ethical considerations that come with implementing the power of AI. For instance, existing AI tools can have internal biases that are very difficult to detect. One example of this is an artificial intelligence contact center with biases or blind spots toward people with a particular accent. Startups may find themselves facing issues like this.
Another important thing to consider is that questions remain about how governments might regulate artificial intelligence in the future. This possibility presents some risk for companies that choose to make a heavy commitment to artificial intelligence.
But what else does AI mean for startups? It also means improvement in the functionality of systems.
AI is Improving Contact Center Software
Though there are potential threats and uncertainty, AI is also improving functionality in previously flawed systems.
I am still proud of declining, in 1987, to invest in one of the first so-called Call Director systems. At the time, I felt they would be too mechanical and unable to provide the help people needed. Since then, systems that walk me through many questions have often frustrated me. “If this is your problem, press 1; if that’s your problem, press 2.” Ninety-five percent of the time, none of the options addresses my problem, and I end up screaming for an operator or a supervisor.
But now, AI has the potential to create extremely intelligent telephone answering software. These systems are called contact center software, and many companies are developing them.
Here, from VoiceSpin, Inc. are some of the top Contact Center solutions:
VoiceSpin offers contact center software for sales and customer service teams.
DialPad offers an “all-in-one customer communication platform with Ai that takes notes, delivers insights, and helps your team stay productive.”
CloudTalk “helps sales and support teams eliminate international calling headaches, reach more prospects, and boost customer experience with:
- Crystal clear call quality
- Localized numbers from 160+ countries
- AI-powered analytics
- How will investors view artificial intelligence?
Startups Should Be Aware of the Advantages and Barriers
What does AI mean for startups? It also means that investors will pile in on some companies if they believe they can create a significant first mover or other competitive advantage. But I also think many investors will adopt a wait-and-see approach. The potential for regulation could be a barrier for some investors. The difficulty of rooting out internal bias from AI systems could be a concern. And there may be a “live by the sword, die by the sword” concern. That is, while AI may make it easier to create certain kinds of companies, it also may make it easier for new entrants to create companies with a stronger competitive position. What’s to keep a competitor from telling its AI system, “Here’s a description of everything the XYZ company is doing. How do we build a more competitive company?”
Another problem facing investors is knowing what potential competitors might be doing.
The Challenge of Integrating AI into Existing Corporate Systems
An article in the Harvard Business Review, titled “The Dumb Reason Your AI Project Will Fail,” points to two important factors that make it difficult to integrate the power of artificial intelligence into a company. The first is simply the difficulty of integrating artificial intelligence with existing company procedures and software. Most AI systems do not have the interfaces to integrate smoothly with existing functions. Secondly, finding people with the knowledge required to pull off this integration is difficult. For these reasons, we may find that artificial intelligence has a learning curve and that improvement will not be immediate.
There are many possible answers to the question, “What does AI mean for startups?”. Being aware of the potential opportunities, as well as threats while considering potential barriers and risks will give your startup an advantage.
I’ve also launched a new course covering everything you need to know to write the best pitch deck for your startup and you can find out more about it here.
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