In our professional practice, we encountered two polarized opinions on AI and its impact on work roles and business models. On the one hand, they are worried about the surge in unemployment and the takeover of artificial intelligence, while on the other hand, they believe that AI will not bring any major changes and will eventually become a bubble.
With 64% of CIOs placing high hopes on using AI to enhance their business operations and grow their businesses, it becomes especially important to understand the powerful capabilities and limitations of technology. Can artificial intelligence really introduce entirely new business models, or are these expectations stemming from bias?
As always, the real answer lies in between.
Then, each technological revolution transforms work roles and workplace routines. The evolution of AI promises to quickly transform the workplace and drive social change. It turns out that AI does not affect society as expected, but society can and should affect AI.
The slowdown in LLM development and the ongoing reports of AI hallucinations make it clear that we know that today’s AI systems are not only far from perfect—they don’t provide what they expect, but developers know that. It is important to understand that the problem is not on artificial intelligence, but on the hype around it. Rather than slowing down and focusing on improving existing features, developers are starting to target the next goal. As a result, many potential problems remained overlooked and ignored, causing many issues, such as Google experienced a $100 billion stake decline as its Bard AI made a factual mistake that no one has checked.
These results suggest that if AI needs control and monitoring to perform basic tasks, it is too early to trust it through complex tasks. Many job roles require insights, critical thinking and flexibility that AI lacks – and that won’t change anytime soon.
As the former head of Openai’s AGI preparation group said, the true efficiency of AI will be the result of a strong dialogue between businesses, governments, industry voices, professionals and citizens. At present, this conversation has not begun, and this will require all the relevant conversations.
AI in a business model: Exploring current value
While the era of AI-driven business models is not what we should expect in a year or two, it is undeniable that artificial intelligence has greatly influenced the way companies operate and manage their workflows.
Usually, it all boils down to three support pillars of any business:
1. Data Analysis
The more we have, the more data we have. This is especially true for businesses – a variety of databases, documents, papers and screenshots are generated every year in business trips. Each of these bits has great value, but must be found first. For human experts, it will take months (if not years) to mine and organize all data. But for AI, it’s a few days, if not seconds. By delving into large amounts of data, sorting them out and organizing them (including unstructured data), AI connects important information to employees, decision makers, and executives, removes data bottlenecks and enables Sharper decision making at each level. With AI, the history and overall perspective of the business journey becomes clearer, adding more certainty and helping business leaders realize the milestones they are in and the milestones they need in the future.
2. Personalization of customer interaction
With the quality of customer experience, the quality of experience in the United States has reached an all-time lowest level, reducing response time, achieving personalized interactions, and addressing customer concerns as soon as possible has never been more important to the company. But achieving these goals means collecting data per customer: demographics, purchase history, brand interaction frequency, and many other factors. There are too many tasks at this scale for a call center or support team, but it’s a daily activity for an AI assistant. By working on an AI-powered platform, and human employees can provide excellent customer service by immediately studying individual customer histories and meeting their specific needs. This approach provides the level of personalization and empathy that customers seek in the brand, strengthening relationships with suppliers and fostering loyalty.
3. Risk Management
Risk management is a constant and ever-changing pain point for a business – it will remain that way forever. The stronger the business landscape, the more situations the executives need to evaluate to properly assess financial and reputational risks. Some assessments are based on critical thinking and experience, while others require a lot of historical data to reveal patterns. In the latter case, AI provides a huge help by handling anomaly detection, identifying patterns and detecting suspicious behavior. These abilities relieve managers, analysts and executives of pressure, allowing them to identify threats and prepare accordingly before they appear.
The future of AI business model: Please continue to pay attention to more
One of the most important points to consider is that the type of AI-driven business model will remain uncertain until the full value of AI is discovered. As business leaders are still on the fences that calculate AI ROI, exploration and research are needed.
The adoption of artificial intelligence is not a small change. It introduces a completely new workflow. Therefore, business leaders need to have a good understanding of this workflow, identify their KPIs, identify reasons that differ from previous routines, and derive the value of change based on their analysis.
For example, in many cases, AI not only improves enterprise processes, but also creates new enterprise processes that allow the expected results to be achieved. But to maximize the value of these results and lay the foundation for a completely new model, any business needs three integral components: process, technology and the people who use it.
