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Have you ever watched a young child begin to learn? Whether they are learning to walk or form a sentence for the first time, every child learns and responds to their environment in a unique way. To me, this is the simplest analogy to explain how “ChatGPT” works.
How Do AI Models Like “ChatGPT” Work?
Any AI program divides information into parts and links them together to provide the most logical responses based on the available datasets. When it comes to usability, how each algorithm responds is what differentiates the program from its competitors. Let’s be realistic, most companies aren’t currently trying to pass the SAT or any other standardized test.
Why Understanding Outputs is Crucial
Standardized tests are an easy way to explain differences in performance between large language models. But for businesses, the more important aspect is how to understand the outputs and use them in decision-making. If you don’t understand the logic behind the model’s response, you’re unlikely to feel confident relying on it to solve problems or provide customer service.
The Role of “DeepSeec” in Cognitive Thinking
This is where “DeepSeec” comes in. The cognitive thinking it provides helps to give a clear explanation of how it arrives at a specific response, making it the preferred program for many business users. With its detailed responses that provide a clear understanding of the cognitive process, humans—who are the key element in the equation—can interact with these algorithms more effectively.
Why Clear Explanations are Vital in AI Models
This is crucial because, as we all know, simply saying, “Trust me – this is right” is not enough to convince managers or leaders without supporting evidence. Despite the current advanced algorithms, the final decision still lies with humans to determine how AI should be integrated into the organization.
Digital Transformation: How AI Drives Growth and Innovation in Business
How AI Can Stimulate Digital Transformation in Business
I recall working with a company in the hospitality sector that used a traditional database to manage customer relationships. They relied on an external service provider for the database, used Excel for reporting, and applied business intelligence techniques. The team had only two weeks to respond to data requests, and they only had general marketing performance reports across all vendors. The company quickly realized that it lacked the necessary data and resources to respond immediately to customer needs. Due to continuous delays in providing data and generating reports, the leadership teams agreed to implement a full-scale digital transformation. The main goal was to facilitate access to information, and AI was simply “the cream on the cake that took too long to bake.”
Digital Transformation Enhances Efficiency Across Departments
Through a precise consulting strategy, the company identified key areas that could benefit from this transformation, opening new pathways in IT, marketing, customer service, vendor management, human resources, and facilities. Given the interconnected nature of the company’s operations, the decision to focus on IT, marketing, and HR and facilities took priority. The technological transformation was the easiest step to move the infrastructure to a more advanced platform across the company, enabling real-time access to data and reporting, as well as facilitating integration and communication with service providers.
The Unique Approach of the Marketing Team
However, the marketing team took a different approach. Instead of relying solely on customer service teams and CRM suppliers to understand customer desires, they discovered they lacked any mechanism for segmenting their customer base. After a thorough analysis, they were able to divide customers into first-time visitors, loyal customers, and past clients. They also identified patterns that attracted customers to specific locations and events. Although they succeeded in achieving their goal, this discovery opened their eyes to their ability to make significant improvements in their marketing strategies.
Improving Customer Targeting and Applying AI
When the marketing team shared these results with IT teams, they realized that the solution lay in simplifying the database to ensure optimal communication with the right customers. These results also allowed for the unification of operational teams with vendor lists that had specific communication requirements. The marketing team worked with internal data teams to develop customized algorithms to identify target customers, timing of messages, selecting appropriate channels, and crafting effective content. Large language models were used for headlines and content, while AI algorithms identified the remaining contact details.
Cost Efficiency: The Real ROI
The largest cost was in analyzing customer behavior, not in selecting the “DeepSeec” or “ChatGPT” model. The highest return on investment wasn’t in choosing a specific model but in solving the core problem of customer segmentation. As a result, AI-powered marketing campaigns saw a 400% improvement in performance, saving significant time for the marketing team and boosting their efficiency.
The Road to Success: Building on Successful Insights
What contributed to the success of this company was its realization of the need to continue building on successful insights. This is often overlooked by many companies in their pursuit of AI application. Since many current tech infrastructures are geared towards deploying “black-box” models, there is an opportunity for companies to skip some of the steps that the hospitality company I mentioned earlier went through.
AI-Driven Digital Transformation: A Holistic Approach is Key
If we return to the analogy of the child, we don’t expect the child to just learn words and stop there. They develop from recognizing sounds and meanings, and when exposed to the outside world, they will start forming complete and organized sentences. Similarly, a company’s AI-driven digital transformation should be comprehensive and not limited. Small changes in isolated functions will not yield the ROI companies are aiming for. When one area improves, building on that to ensure widespread value can be the best approach to guarantee ROI. This doesn’t depend on choosing a specific AI model but on the actual value being delivered to customers.
Sources:
- Artificial Intelligence and Digital Transformation in Businesses – Harvard Business Review
- Customer Segmentation Using AI Models – Insights from McKinsey
- Digital Transformation Strategies in the Hospitality Industry – Deloitte