According to data from the Federal Reserve Bank of St. Louis, generative artificial intelligence (AI) saw adoption rates of over 39% among Americans aged 18 to 64, two years after the public release of OpenAI’s ChatGPT.
Additionally, 28% of the same age group have reported using generative AI specifically for work. Professionals in the fields of marketing, sales, customer service, product development, human resources, and finance are among those who possess high levels of expertise in the use of AI globally.
Even though adoption rates and proficiency in AI are high, there are businesses across the globe that still have doubts on fully embracing AI due to the costs associated and roadblocks associated with AI adoption.
Roadblocks
Aside from the financial cost of adopting generative AI tools, there are a few factors that prevent enterprises from fully integrating AI into their operations.
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Data Leaks
Since generative AI models need to be fed massive amounts of data, companies who run these tools face the risk of falling victim to data leaks, regardless of whether this happens by accident or a targeted attack by cybercriminals.
Breaches can result in unauthorized access to sensitive information such as customer data and proprietary information that’s unique to an organization.
There is also concern about internal data being used to train models made available to others. While a number of the enterprise solutions promise that this doesn’t happen, enterprises need to consider their liability and obligations to users and clients.
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Employee Perception
Another risk that’s preventing enterprises from adopting AI boils down to employee perception.
Workers could interpret the adoption of AI tools or the onboarding of talent with AI skills as a sign of potential layoffs.
While this concern is valid, both workers and organizations need to realize that there’s lots of work to go around, and at this point, AI exists to help users eliminate the mundane and low value portions of their job.
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AI Hallucination
Hallucination occurs when a generative AI chatbot, powered by a large language model (LLM), creates outputs that are nonexistent or totally inaccurate.
Even though AI tools have seen massive strides in terms of output, there are still instances where AI algorithms will produce outputs that aren’t factual nor based on training data and the information given in user prompts.
Given these issues, how can enterprises fully embrace AI?
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Part of the answer lies in bringing in workers (full-time or independent) who are proficient in leveraging generative AI tools.
Case in point: Workers who possess AI skills are more likely to know how to deal with issues such as hallucination.
Tech- and AI-savvy workers are also just as likely to make use of AI on a particular problem instead of treating it as a solution to every work-related task or challenge.
Last but not least, those proficient in AI are more likely to be knowledgeable on data security risks associated with AI use, putting them, and the organizations they are working for, in a position to mitigate those problems.
Leveraging AI to Prepare for the Future
In a world that’s being shaped yet again by another technological innovation, it’s crucial for businesses to start thinking about how they can integrate AI into various levels of their organizations despite the risk factors associated with it.
One of the ways an organization can mitigate the risk of leveraging AI is by hiring tech-savvy professionals who possess the knowledge and skills needed in the utilization of generative AI tools.
Professor Joel Litman and Dr. Mark L. Frigo in the book, “Driven” emphasized the importance of identifying the services a firm needs based on its goals and engaging the right personnel in the achievement thereof.
As generative AI becomes better, it is reasonable to assume that adoption will become a necessity for businesses. That’s why enterprise leaders shouldn’t set aside AI adoption and recruiting those who are proficient in the use of AI tools.
The more enterprises drag their feet on this, the higher the chances that they will get left behind in the years to come.
If you’re looking to gain a better understanding of Return Driven Strategy and Career Driven Strategy, we highly recommend checking out “Driven” by Professor Litman and Dr. Frigo.
Click here to get your copy and learn how this framework can help you in your business strategies and ultimately, in ethically maximizing wealth for your firm.
About The Dynamic Marketing Communiqué’s
“Tuesdays: Return Driven Strategy”
In the book, “Driven,” authors Professor Joel Litman and Dr. Mark L. Frigo said that the goal of every long-term successful business strategy should incorporate the combined necessity of “making the world a better place” and “getting wealthy.”
That is why they created Return Driven Strategy and Career Driven Strategy—frameworks that were built to help leaders and professionals plan and evaluate businesses so they can also help others achieve their organizational goals and career goals.
The frameworks describe the plans and actions that drive returns for anyone in an organization such as independent contractors, marketers, brand managers, communicators, and other people in any field. These actions lead to the creation of wealth and value for customers, employees, shareholders, and the society.
Every Tuesday, we’ll highlight case studies, business strategies, tips, and insights related to Return Driven Strategy and Career Driven Strategy.
In planning, building, or managing brands and businesses, these strategies, case studies, and guidelines will help you choose what specific actions to take and when to take them.
Hope you find this week’s topic interesting and helpful.
Stay tuned for next Tuesday’s “Return Driven Strategy!”
Cheers,
Adrian Kyle Vergara
Content Writer
Valens Dynamic Marketing Capabilities
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