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Answering the Big Questions about What AI Means for Your Company

With the emergence of generative artificial intelligence came an influx of questions and requests for Anu George, digital transformation leader and COO of the media analytics organization PublicRelay: “What do you know about this? Are these capabilities a myth? Can it do that? What is this?” 

Generative AI models, such as ChatGPT, have reached a point where they will dramatically reshape our personal and professional landscapes, impacting the world at large. According to George, every business leader, at nearly every level, must comprehend how to leverage AI to drive their organization’s success. This technological advancement is not merely game-changing, but era-defining, akin to the emergence of the World Wide Web over three decades ago. AI is here to stay and embracing it sooner rather than later is the prudent path forward.

Understanding What AI Is and How It Works for You

Despite the growing prevalence of artificial intelligence within our organizations, many of us still possess only a minimal to moderate understanding of this technology. AI is already being utilized in various capacities, such as assisting with email composition, yet most employees remain unaware about how their companies are leveraging these intelligent models. This knowledge gap presents an opportunity for deeper comprehension and awareness.

George categorizes AI into two primary types: traditional and generative. Traditional AI systems have been around for some time, exemplified by the chess-playing programs that have long competed against human players on desktop computers. These AI-powered systems generate the moves for the computer’s side of the game.

In contrast, generative AI represents a more recent technological advancement, gaining widespread recognition and acclaim with the launch of the large language model, ChatGPT. According to data reported by The Wall Street Journal, (sourced OpenAI), “92% of Fortune 500 companies are using ChatGPT in some form, and 100 million people actively use ChatGPT every week.” Beyond ChatGPT, other prominent large language models like Anthropic’s Claude (George’s preferred model), Google’s Gemini (formerly Bard), and Lama are also gaining significant traction.

GPT, which stands for “Generative Pre-trained Transformer,” is the underlying architecture that powers ChatGPT and other large language models. These transformer-based neural networks are trained on massive text datasets, that allow the models to develop a deep understanding of language, including syntax, semantics, and pragmatics. This allows the models to generate human-like text, understand context and nuance, and engage in fluid, coherent conversations. Leveraging user feedback and input, the GPT model can continuously refine its outputs, creating more tailored and relevant content or performing specific tasks more effectively.

Traditional AI models, in contrast, rely on predefined rules, structured data, and supervised learning, making them well-suited for specific tasks like Tesla’s self-driving system, though they require substantial annotated datasets and offer higher transparency compared to newer generative AI approaches.

The Impact of AI in the Modern World and the Workforce

Although neither traditional nor generative AI possesses true “intelligence,” since they are essentially mathematical predictive models, AI is transformative in its ability to analyze vast amounts of data and predict future outcomes, user needs, and preferences.

Traditional AI systems excel at specific, structured tasks like the recommender algorithms used by Netflix and TikTok to suggest content based on user behavior. These techniques are also applied in areas such as fraud detection, email spam filtering, and consumer behavior forecasting. Generative AI, like OpenAI’s ChatGPT, is trained on vast, diverse data which allows it to generate new content, adapt to various contexts and handle unstructured data. That is why Generative AI is great at summarizing data, extracting information, writing poetry, or engaging in human-like conversations. For example, you can provide it with a complex legal document and ask the model, “Can you summarize this document for me?” 

Although Generative AI is highly effective, it remains fundamentally a mathematical model and lacks true intelligence. This limitation can lead to “hallucinations,” where it generates plausible yet incorrect information. Businesses must therefore rigorously validate this output to avoid potentially harmful consequences.

AI models increasingly provide advanced insights and enable automation of several manual tasks in an organization, but their use also introduces new data security vulnerabilities. Generative AI systems like ChatGPT, if not properly secured, can be exploited to generate deceptive content or access sensitive information. Businesses must address these emerging threats through rigorous data governance and employee education. Companies must also educate their workforce and establish clear policies to prevent the sharing of proprietary or protected data, interacting with generative AI models.

The Consequences and Conclusions of AI

Generative AI models demonstrate transformative potential, capable of generating immense value to organizations. Thoughtful, strategic planning is essential for leaders to capitalize on AI’s benefits. However, the technology also introduces significant risks, from inaccuracies to data security breaches, necessitating a cautious, ethics-driven approach to deployment and use.

That’s why it’s vital to understand how it works, how to protect your data, and how to strategically adopt AI within the company. 

  • The use of AI should be an integral part of the strategic planning process of an organization.
  • Companies must invest in educating their employees about AI’s potential and ethical use. This includes setting up oversight committees to monitor AI implementations.
  • Businesses must establish clear guidelines on AI use, focusing on data privacy and security. 
  • Maintaining transparency in how AI systems impact the company’s strategy, especially in high-stakes areas like hiring, financials, or customer service, is vital. Systems should be explainable and accountable.

The board should continually participate in the broader conversations about the ethical development, implementation, and deployment of AI. Everyone in leadership at the company should be committed to transparency and continuous learning and adaptation. Guided by leaders like George in this field, every company can start today by forming responsible AI practices that contribute positively to a future where technology enhances humanity’s best qualities.