Artificial intelligence (AI) washing is a marketing strategy in which sellers represent their products as using AI technology, when in fact they don’t or just have a tenuous link to it.
When marketing professionals exaggerate a product’s AI capabilities in order to increase sales, this is known as AI washing. Similar to “greenwashing,” which occurs when a company’s management team makes unsubstantiated, erroneous, or deceptive claims about the sustainability of its goods, services, or business practices, AI washing is the same.
Businesses frequently engage in AI cleaning because:
They are seeking funding
Investors are constantly searching for the trendiest trends, and technology with AI capabilities fits the bill. Investors are therefore all seeking initiatives to back the use of AI.
This implies that entrepreneurs in the technology industry, in particular, have an incentive to utilize AI washing because it makes it much simpler to obtain investor backing.
They are stalling for time
Some businesses that engage in AI washing do so with the intention of providing AI goods and/or services. They act as though their goods or services already have AI functionality, but they haven’t quite gotten there yet.
They Lack an Understanding of AI
Despite the enormous promise of artificial intelligence, businesses frequently misrepresent it because they don’t completely comprehend it. It can be challenging for corporations to distinguish between what genuinely falls under the umbrella title of “AI” and what doesn’t because it encompasses a wide range of tools.
To identify whether vendors have actual AI capabilities, businesses must assess a number of factors, such as:
Knowledge of the staff
Potential clients should confirm that the staff members of their vendors have substantial experience in artificial intelligence and deep learning.
Mathematicians, architects, data scientists, and engineers must be employed by vendors who advertise their AI goods and/or services.
These staff members create the models and train the machinery to comprehend diverse scenarios, predict their impacts, plan actions for the future, and learn from the outcomes.
The Data
For AI-based systems to function effectively, enormous volumes of data are required. Therefore, prospective customers must consider the volume of data that IT vendors gather and make sure that it comes from a variety of sources.
Be Sure the AI improves over time
Real artificial intelligence improves with time. In order to understand how suppliers’ AI software improves and what decisions the AI is capable of making, potential clients should ask them.
Additionally, businesses should ask providers how much connection with humans is required and whether AI can support the job of human employees.
AI and people can accomplish more when they work together than when they do so alone. If the vendors are unable to completely respond to such queries, they are probably washing the AI.
Make the Right Inquiries
Self-described AI vendors should be approached by buyers with a strong grain of suspicion. Assume they aren’t offering AI-related goods or services, and let the vendors substantiate their claims.
Customers should inquire about the precise artificial intelligence technologies being used by vendors and how they intend to stay current with this technology.
To avoid confusing end-user firms, an increasing number of startups and established vendors refer to themselves as “AI vendors” and assert that they provide AI goods and/or services without describing how their selections differ from the thousands of others now available.
Vendors should compile case studies that detail the quantitative outcomes their clients have accomplished with artificial intelligence to gain the trust of these clients.
Bottom line
It’s imperative that these vendors correctly define “AI” in their sales and marketing materials, spell out how their AI solution differs from that of their rivals, and specify precisely what issues it resolves for clients.
Additionally, AI vendors must demonstrate to customers that their employees possess the qualifications required to carry out AI-related jobs, such as an understanding of programming languages, neural network topologies, statistics, linear algebra, and signal processing methods.
Instead of just providing cutting-edge technology, vendors must show prospective clients how their AI software can enhance process automation and decision-making, as well as provide solutions that aid in the resolution of their business challenges.
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