AI, the shift from content generation to decision making

nairobi kenya
Nairobi, Kenya.

It was in November 2022 that we saw OpenAI introduce ChatGPT which stands for chat Generative Pre-trained Transformer, a large language model-based chatbot that enabled users to refine and steer conversation towards a desired length, format, style not to mention language.

Exactly a year ago, we saw the dawn of AI but where exactly is it going in the next year or two, considering the leapfrogs in development that we have seen in the AI space?

So where exactly is Ai headed?

The next step in AI should be a move from normal content creation and analysis into decision-making which most likely will include workflow automation.

We are likely to see the use of the Large Language Model backbone of generative AI shift towards using a more domain-specific language model.

Contributing to this point is Zuko Mdwaba, Salesforce Area VP / Africa Executive who noted how desk work estimated generative AI will save about five hours a week in the future.

“Chatbots and virtual assistants will simplify the employee experience by automatically booking the right space for a team’s needs. AI will also provide quick responses to inquiries, guide employees to resources, and facilitate service requests.”

Businesses will transform the way they measure performance and productivity to focus more on outcomes instead of inputs.

Mdwaba anticipates a surge in businesses adopting semantic query capabilities with the emergence of structured data (in the form of sales figures and customer demographics) and unstructured data like blogs, and social commentary.

Overall, data volumes are projected to increase by an average of 23% over the next 12 months, according to Mdwaba and teams are in a race to ensure the quality of the data underlying their generative AI initiatives before their competitors do.

He says investing in technical solutions that will harmonize data sources while reducing data gravity is key as teams pay more attention to defining data governance protocols while cultivating strong data cultures among their teams.

It all boils down to the “ethical, and transparent use of generative AI [which] may be what sets companies apart in customers’ minds,” concludes Mdwaba.

What is the upshot?

Expert tech editor Marcus Moloko notes the importance of navigating the evolution of AI with the focus being on ethical transparency and collaboration between users and AI systems.

What does this mean?

It all means AI is evolving at light speed, well not necessarily light speed but a relatively fast pace.

We will see content generation and analysis shift into more solid decision-making in the following ways:

More refined advanced machine learning models, which include more complex patterns and overall relationship to data, enabling AI to understand and generate more nuanced content.

Think of Elon Musk’s Grok, AI most likely to show personality when responding.

All incoming future models will come packed to handle complex patterns and relationships to data, enhanced natural language processing capabilities in order to understand more human-like language.

We are more likely to see AI systems able to come with contextual understanding, which means the ability to interpret and respond to subtleties of human communication.

A definite will be the integration of AI into business processes.

We should see better collaboration between users and AI systems, as AI systems take on a more solid role in decision-making roles.

This is imperative as this collaboration will allow seamless interaction.  Any resistance in businesses will likely delay needed technological momentum and growth.

The case in point is that AI continues to show growth and that growth shows that we will all witness more sophisticated decision-making capabilities and increased integration of AI in business processes.  Transparency and collaboration are key.

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Featured image: Amani Nation on Unsplash



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