Many companies are hesitant to implement artificial intelligence for fear that AI engines will expose their proprietary data to other companies, including competitors. At the same time, some companies want to deliberately insert their data into AI engines as part of brand building. Is this a billion dollar opportunity or (another) fatal flaw in the evolution of AI?
This counterintuitive idea was born during a panel discussion hosted by NextAccess, a consulting firm that advises clients on how to best leverage AI to improve strategies for bringing products to market and generating revenue. Ta.
Let's start from the beginning. Simply put, an AI engine has two components. The first is an extensive content database called a large-scale language model (LLM) that contains all the information an AI company can find. This includes Wikipedia, the New York Times, and all other public content. (There is a growing serious debate about copyright infringement, but that's a topic for another day.)
The second component of the AI ​​engine is an algorithm that uses LLM data to create responses to queries. When you ask the AI ​​engine to complete the sentence “The dog…”, the algorithm checks his LLM to see how often this fragment is already present and what common words complete the sentence. It then provides the user with the statistically most likely next word. In this case, “hill” is a typical response, but “casserole” is not.
Companies looking to leverage AI can start by asking questions. For example, an apparel company might ask, “What are the latest trends in men's shoes?” But just by asking this question, the AI ​​engine knows that the apparel company is considering new products in that category, information the company wants to hide from its competitors.
To use AI more effectively, companies upload a piece of data (customer responses or sales history) and ask the AI ​​engine to find patterns and compare it to other information in LLM . However, many AI engines add uploaded company data to his LLM, so if another company representative asks exactly the right questions, he can generate a response that reveals this data. Most AI companies have policies and other protections in place to prevent this data breach, but some recent studies have shown that 60 to 60 companies are concerned that these protections are insufficient. 75% have outlawed the use of AI. (There are many other reasons why companies are hesitant, but data privacy consistently ranks at the top.)
Despite these corporate bans, every company in the world has at least one employee who has used an AI engine, perhaps on a personal computer not affiliated with the company, to solve a business problem. I think it is.
In the NextAccess panel discussion, one of the participants runs a consulting firm. In direct contrast to most other companies, she actively wants her company's data inserted into her LLM. Especially if you can somehow connect the data to your brand name. When someone asks her AI engine a query that her data would improve the response to, she hopes the person asking the question will see her company as a source of wisdom, which can drive new customer engagement. Masu.
Putting a company's wisdom and brand in front of information seekers is not a new concept. Search engine optimization (SEO) is the practice of making your company's website more available to search engines such as Google so that your company's web links appear in more Google queries. This practice has spawned an entire industry of consulting and technology companies that can help brands design their websites to take full advantage of Google's scanning tools. Businesses can also pay Google to display their web links at the top of pages for relevant queries. Importantly, these “sponsored” results are clearly marked, so internet travelers know which Google responses are based on organic content and which are based on company payments. can do.
Google has instilled in all of us that search engine results don't always provide the right or best answer to a question. Clicking on multiple links to explore source sites has become a normal and expected routine for web searchers.
Users of AI engines now have different expectations. They assume that the AI ​​engine is providing the best possible answer. Known AI flaws, such as bias and hallucinations, are also occurring less frequently with newer, more powerful AI engines. User trust in AI accuracy is increasing.
The pull of additional revenue persuaded AI companies to reveal some of their algorithmic secrets and create the AI ​​Engine Optimization (AEO) industry, allowing AI companies to rearrange data in particularly invasive ways. Will it happen? Will LLM increase the likelihood that your company's data and brand will be referenced in AI responses to user queries? The AI ​​engine will offer paid placements (ideally Does it offer sponsored content?
And how will AI users react? Will they appreciate better and more specific answers, or will they question the objectivity and neutrality of AI companies? These unanswered questions demonstrate that AI is different from previous technological tools and, therefore, the path it will follow is still undefined. stay tuned.