How Has the Integration of AI and Machine Learning in Business Management Boosted the Revenue of MNCs?

Key takeaways:

• Introduction
• Role of AI and ML in marketing and sales
• AI and ML for cybersecurity and customer relationship management

Running any business or organization means handling different tasks to achieve its goals. Over the years, the integration of digital technologies in business management has helped companies simplify various planning, scheduling, and execution processes. The emergence of Artificial Intelligence and Machine Learning has further helped firms improve the outcomes of business administrations at all levels, including policy formulation, workflow management, customer relationship assessment, and marketing strategy planning. With globalization and trade expanding, the demand for AI and machine learning in business management and administration is expected to rise.

Rising Adoption of AI and ML in Marketing & Branding

In recent times, the role of AI-powered tools has increased significantly in market research operations. AI, with its advanced language models, can quickly process large amounts of data much faster than traditional computing methods. Along with this, AI programs embedded with machine learning algorithms aid in predicting the upcoming trends in the market, thus helping businesses frame customer-centric ad campaigns.

Moreover, enterprises have started deploying these digital tools, along with data analytics applications to study the demographic, sociocultural, economic, and political factors impacting their business operations. Based on the insights gathered by these ML algorithms, companies formulate their strategies, thus helping them mitigate the challenges and problems that are likely to arise in the near future. In a survey conducted by McKinsey, a leading management consulting company, 65% of the respondents stated that their business had adopted advanced generative AI tools for sales and marketing purposes, thereby highlighting the increased dependence on these emerging technologies. Several business management studies have shown that the use of predictive analytics models has improved the decision-making capabilities of businesses significantly.

Another important advantage of integrating AI and machine learning in business management is that they help automate the repetitive tasks in various business operations, thus increasing the efficiency and productivity of the company. Also, as human intervention decreases, accuracy improves. Freed-up labor can focus on creative tasks, making workflows smoother. This reduces costs and boosts profitability.

Machine Learning in Fraud Detection & CRM

In the last few years, the growing penetration of 5G services across the globe has contributed to the expansion of the e-commerce sector. A majority of businesses in various sectors of the global economy have started offering their services through online websites. Though this shift toward digital platforms has helped them cater to a larger consumer base, issues regarding cybersecurity and the safety of customers’ data have restricted the growth of these web-based businesses. To address these problems, companies have started deploying AI tools for threat detection and response actions. The natural language processing (NLP) techniques embedded in these solutions proactively detect any anomalies in network traffic, thus enabling companies to identify phishing attacks.

Moreover, the analysis of historical data, system configuration, and usage patterns using machine learning algorithms helps companies find out the vulnerabilities in their system that the attackers might try to exploit in the event of a cyberattack. By identifying the flaws in their platform, AI assists companies in increasing their resilience and robustness in the long run. These technologies enhance data security, strengthening AI and machine learning’s role in business.

Along with this, machine learning algorithms are also deployed to design advanced chatbots which aid consumers in getting their queries resolved. These grievance redressal mechanisms are built on natural language understanding and NLP models which offer personalized customer services to the users, thereby improving brand loyalty. Many e-commerce companies have partnered with generative AI companies to develop multilingual chat windows for their audience base.

Winding up, the growth of the AI and machine learning in business sector is attributed to the various advantages offered by these innovative technologies in simplifying the administration in large companies and organizations. The growing deployment of AI tools for cybersecurity and customer relationship management is anticipated to drive industry growth in the near future.

For more information on the leading growth drivers and investment opportunities in the landscape, contact our experts here!

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