Intetics CEO Boris Kontsevoi Highlights the Success Potential of Conversational AI in Business

Boris Kontsevoi is a technology executive, President and CEO of Intetics, a global software engineering and data processing company, shares the steps to unlock the potential of Conversational AI and build it as a successful business model.

Artificial intelligence (AI) has rapidly evolved from a concept in sci-fi movies to a ubiquitous presence in daily lives. Chatbots and computer vision technologies have become integral to standard business processes, revolutionizing industries ranging from high tech and telecoms to finance and healthcare. Market research indicates that the global AI market is projected to exceed $500 billion by 2030, with IDC forecasting a valuation of over $500 billion by 2024. The time has come to explore the reasons behind this remarkable growth.

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The roots of modern AI trace back to 1956, when John McCarthy coined the term “artificial intelligence” during a computer workshop at Dartmouth College. Initial AI research in the late 1950s and early 1960s focused on developing systems capable of emulating human intelligence. Symbolic AI and connectionism, the initial neural networks, formed the primary areas of exploration.

However, government funding was cut off in 1974 due to perceived complexities. The subsequent AI winter ended in the 1990s and 2000s, with a resurgence of interest in artificial neural networks. Today, advancements in computing power, novel algorithms, and the availability of vast amounts of data have paved the way for systems capable of interpreting complex information, autonomous learning, and near real-time decision-making.

While conversational AI and virtual assistants have streamlined and simplified daily tasks, concerns about their reliability have emerged. These AI systems, powered by natural language processing (NLP) and machine learning algorithms, are designed to understand and respond to user requests, functioning 24/7 without productivity losses. However, vulnerabilities and biases within the underlying system can pose risks. Generative technologies have the potential to propagate disinformation, cater to conspiracy theories, or serve as uncritical information sources. Trust in AI is high, reminiscent of the reliance on Google for information searches. But is this trust well-founded?

It is essential to recognize that AI systems derive their performance from the data they are trained on. If the data is skewed or incomplete, the outputs will inevitably reflect biases and limitations. Furthermore, in certain scenarios, AI may be granted excessive autonomy without adequate human supervision, leading to unforeseen or detrimental consequences.

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Despite these challenges, a McKinsey survey revealed that more than two-thirds of consumers trust AI-based products or services as much as, if not more than, those relying primarily on human input. To unlock the full potential of conversational AI for businesses, integration across various platforms, such as messaging apps and voice assistants, is crucial. This accessibility allows companies to automate customer service, personalize communications, and gather valuable data. Conversational AI finds application across multiple sectors, including customer services, healthcare, e-commerce, education, and finance.

Developing a successful conversational AI business model entails several key steps. First, defining a niche and creating a high-quality product that can communicate naturally, comprehend complex queries, and provide accurate responses are vital. The AI machine must possess the capacity to handle a large user base and be trained with machine learning algorithms.

NLP tools may also be required to enable natural language understanding and accurate responses. Integration with existing systems, such as CRM, ERP, and help desk software, enhances capabilities and streamlines customer support, workflows, and personalized experiences.

The final step involves devising a comprehensive go-to-market strategy, encompassing target audience definition, analysis of their needs and preferences, and the development of a tailored marketing plan. Regular monitoring and optimization of conversational AI systems ensure they meet user requirements and improve performance. Leveraging analytics tools allows for data-driven insights into customer interactions.

Furthermore, a customer guarantee for outstanding support fosters a loyal customer base, positive feedback, enhanced brand image, and customer attraction. It is crucial to remain up to date with evolving trends and technologies in the dynamic AI landscape to maintain a competitive edge.

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