Human Vs. Artificial Intelligence: Why Finding The Right Balance Is Key To Success

Human Vs. Artificial Intelligence

Artificial Intelligence provides huge benefits to both organizations and customers. Customers will receive faster service and a more individualized experience no matter how complicated a query is. Organizations’ CX operations will become more cost-effective, scalable, and efficient by enabling automation. By providing an exceptional customer experience, organizations will ultimately increase their bottom-line revenues.

At the same time, the human element in customer experience must not be overlooked. According to Gartner’s predictions, for instance, a human agent will still be involved in 44% of communication, even though the proportion of phone-based communication will decrease from 41% to 12% of all interactions with customer service.

Some process-based tasks will be eliminated by technology like AI and robotic automation. Artificial Intelligence and automation allow humans to spend more time doing what they do best. Only human agents can think creatively, solve complex problems and do empathetic work. So humans are needed along with Artificial Intelligence

Nowadays, customers place a high value on convenience and efficiency. In client support, for example, individuals need quick and simple responses. My customers would feel at ease speaking with an AI-powered customer service solution if they could speak normally and resolve their issues quickly.

What is the right balance of intelligence between Artificial and human workers?

Incorporating Artificial Intelligence into a business would reduce bureaucracy and increase agility, but automating everything is not the answer. This is because human nature is still more adaptable than AI when analyzing outlier aspects.

In bureaucratic models, decisions can only be made by high representatives, making it too difficult for other members to move the buying or marketing process forward; we have been using technology to make our business less bureaucratic and more agile.

Despite its occasional annoyance, bureaucracy is always necessary to some extent. Beauracry provides a clear guide for business leaders to set guidelines for other teams so that the outcome is as expected. However, at that point, in some cases, it gets lost among many rules and steps.

When AI is used, these machines are programmed to follow the rules, saving you time on repetitive or tracking tasks. However, because machines are programmed to follow the rules, some rules don’t apply in every situation.

Imagine that you had a severe case of COVID-19 and searched for vitamins and other medications to treat it for a few weeks. When you get over this disease, you go back to looking for the things you like to buy regularly: clothes, video games, or anything more amusing than vitamins and medicines.

However, the algorithm recommends COVID medications. What took place here? The algorithm is unable to distinguish between the most common and situational purchases.

If Artificial Intelligence software did all the work, machines might follow the rules without understanding the context, making it harder for customers to find what they want.

Sylvain has discovered the following balance for these two:

The goal is not to eliminate AI altogether but rather to teach our team members how to use it more effectively so that both parties can get the most out of it, as was the case with the industrial revolution.

Why Finding The Right Balance Is Key To Success

Organizations frequently misjudge how agreeable individuals are to man-made Intelligence. According to the survey, 66% of people are content to see a robot at the grocery store cleaning up spills or restocking shelves, and 76% are content to see disinfectant robots powered by AI in hospitals. Organizations achieve more satisfied and productive employees, greater efficiencies, increased cash flow, and many more when humans and Artificial Intelligence work together by finding the right balance between them.

In successful Artificial Intelligence deployments, humans and Artificial Intelligence should play equal roles. Empathy and judgment, which come naturally to people, are difficult for machines to perform, whereas manually analyzing massive data volumes is practically impossible. Humans can understand and learn from past events and incidents. However, Artificial Intelligence is behind in this area due to its inability to think. Both humans and Artificial Intelligence play important roles, but finding the right balance between them makes the organization successful.

Challenges in Finding the Right Balance

While integrating humans and AI can provide many benefits, finding the optimal balance is challenging. One major issue is a lack of understanding of how complex AI systems work and how they will interact with human workers. Poor integration of AI into existing workflows can disrupt processes, cause confusion over roles and responsibilities, and reduce human engagement. Organizations must conduct thorough job analyses and implement change management programs to help workers understand how their roles may change. 

As certain routine tasks are automated, human employees will also need new skills to manage and work alongside AI technologies effectively. Retraining initiatives will help address potential skill gaps, but these transitions need to be smoothly handled to minimize issues. Some resistance to change among the human workforce is also likely as they adapt to working with new technologies. Fears over job losses and a lack of technical expertise may emerge, so organizational culture changes and clear communication about evolving job roles must overcome these barriers. 

Determining the most appropriate allocation of tasks between humans and AI can be difficult, as it depends on multiple context-specific factors. Ongoing reviews will be needed to adjust this division of labor over time. Ensuring tight yet flexible human and AI systems integration through good design, tools, processes, and governance is another hurdle to cross-functional collaboration and balanced centralized-decentralized models. Finally, not all implications of human-AI partnerships can be anticipated, so adaptive approaches, monitoring, and a willingness to course-correct are important to address unforeseen consequences as implementation progresses.

Tips for Finding the Right Balance:

Case Studies: Lessons from Companies That Got the Balance Right

Example 1: Anthropic

The AI safety startup ensures its systems are helpful, and harmless, and consider human values. It works closely with researchers, engineers, and ethicists to design AI that understands its limitations and can learn from humans. By only automating well-defined tasks and keeping humans ultimately in control of riskier decisions, Anthropic has found a collaborative approach.

Example 2: IDEO

The design firm paired human designers with AI assistants to streamline routine tasks like image search and deadline tracking. This freed up human creativity for higher-level strategic thinking. regular training helped the workforce understand the technology. IDEO optimized contribution from human skills and AI capabilities by setting clear roles and oversight.

Example 3: Telus

The telecom moved customer service agents to higher-value work by automating 70% of common queries with virtual assistants. But humans still handle complex issues, provide empathy and help train AI models. Reskilling programs upskilled agents for these evolving roles. TELUS improved cx and workforce productivity and engagement by maintaining a balanced human-AI partnership.


Though AI promises enhanced efficiency, productivity, and innovation, finding the right balance with human intelligence is crucial. Organizations must leverage the strengths of both human workers and AI systems to realize the full benefits. Companies can gain a competitive advantage with humans steering AI to augment capabilities rather than replace jobs. Promoting human-AI collaboration and adapting to continuous AI changes can strike the right balance.