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What business functions will benefit most from AI and machine learning in the future?

Business leaders are optimistic that AI can significantly improve organizational resilience and long-term growth.
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As AI evolves into a transformative force in the business landscape, it grows in potential to address the global challenges of our time. In the latest edition of our Thinking Ahead series, we interviewed industry thought leaders and technology decision-makers to thoroughly explore AI's pivotal role in driving sustainable growth.

Business leaders are optimistic that AI can significantly improve organizational resilience and long-term growth. According to a UST survey on sustainable business transformation, nearly all organizations confidently anticipate AI's evolving role in effectively meeting sustainability goals. They believe AI will increase efficiency, productivity, data security, and compliance across diverse fields in the coming years.

In this article, we look at some of the business functions enabling AI-integrated solutions that have the potential to drive positive outcomes and future sustainability.

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At a glance: Key business functions

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Operations management

The survey finds that 93% of organizations have reported improved operational efficiency by adopting AI and new technologies in the past five years.

AI and ML technologies have enhanced various operational processes, including production planning, inventory management, and resource allocation. AI's major strength lies in its capacity to harness data from diverse sources such as sensors, production logs, and supply chain systems. It analyzes them to detect inefficiencies, forecast demand with higher accuracy, or streamline workflows.

For example, AI/ML algorithms can dynamically analyze real-time data to adjust production schedules, reducing downtime and increasing throughput. In inventory management, AI/ML can predict stock levels and reorder points more precisely, minimizing excess inventory and reducing holding costs. Moreover, through optimized resource allocation, AI/ML ensures that materials and labor are utilized efficiently, reducing operational expenses.

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Supply chain management

Adopting AI in supply chain management helps advance key functions such as enhanced demand forecasting, inventory optimization, or logistics planning. AI provides highly accurate demand forecasts by processing and analyzing vast amounts of historical data, market trends, and external factors. Businesses can better anticipate customer needs and adjust their inventory levels, reducing the risk of excess inventory and minimizing stockouts. By continuously analyzing inventory data, AI/ML algorithms can determine the optimal stock levels for different products, ensuring that the right amount of inventory is available at the right time. This reduces carrying costs and prevents the accumulation of obsolete stock.

Maneet Singh, CIO of Odyssey Logistics, believes AI will represent the frontier of future supply chains. In logistics planning, AI-driven algorithms can be trained on extensive data sets that can optimize routes, manage storage capacity, and adjust real-time variables such as traffic conditions, weather patterns, and fuel consumption based on live data. This optimization level can unlock significant efficiencies across the supply chain, minimizing waste, maximizing productivity, and driving overall sustainability.

The survey informs us that organizations already utilize AI or IT to create more sustainable supply chains. Businesses are most likely to use AI/IT to facilitate better decision-making through data analytics (47%) and support the implementation of circular economy practices (47%).

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Customer relationship management

Machine learning models enhance CRM systems by thoroughly analyzing extensive customer data, including purchase history, behavior patterns, and preferences, leading to significantly improved customer segmentation. By understanding the nuanced differences between customer segments, companies can tailor their marketing and sales strategies to meet each group's specific needs and preferences and provide a more personalized and seamless customer experience. AI's capabilities in predictive analytics can lead to better forecasts of customer behavior. For example, AI can predict which customers are likely to purchase, which products they might be interested in, and even when they make their next purchase. This foresight enables companies to engage with customers and increase customer loyalty proactively.

AI-powered chatbots and virtual assistants can automate customer interactions, handle customer inquiries and transactions, and provide quick and accurate responses 24/7. This can reduce wait times, build company service consistency, and free up human agents' bandwidth to deal with more strategic concerns.

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Marketing and advertising

Intelligent algorithms improve marketing campaign performance significantly while optimizing ad spend. AI refines audience targeting with unprecedented precision, increasing the likelihood of conversion. Personalization is a key component of AI-driven marketing, delivering content tailored with historical data-based insights on customers' unique preferences and past interactions with the brand.

By continuously analyzing the performance of various advertising channels and content, AI-driven insights can determine which ads are performing well, which channels deliver the best results, and how to adjust spending in real time to maximize ROI, leading to efficient ad spend management.

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Human resources (HR)

Several areas benefit from integrating AI solutions into HR functions. For instance, recruitment processes are automating resume screening and interview scheduling. Talent management is optimized by analyzing employee performance metrics, predicting employee turnover, and facilitating internal mobility with a better understanding of the best fit in skills and roles. Employee engagement is a key focus of AI-integrated HR management, which provides real-time insights into employee morale and engagement levels by analyzing employee sentiment through surveys, feedback, and other communication channels. AI-powered personalization can also recommend effective training and development programs based on employee data that help employees meet their goals.

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Predictive maintenance

AI and ML enable proactive maintenance strategies for equipment and assets, significantly enhancing operational efficiency and cost-effectiveness. AI/ML algorithms analyze vast amounts of data generated by sensors, equipment logs, and maintenance records to identify patterns and detect anomalies that may indicate potential failures or inefficiencies. Predictive analytics takes historical maintenance data, operational conditions, and failure patterns to forecast when specific components or systems are likely to fail. One of the key benefits of AI-driven predictive maintenance is its ability to extend the lifespan of assets and improve their reliability. By identifying potential issues early and addressing them proactively, organizations can prevent wear and tear from escalating into major failures.

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Risk management and compliance

AI can transform organizations' identification, assessment, and mitigation of risks with refined anomaly detection and preventive insights. For instance, in cybersecurity, AI can monitor network traffic for signs of suspicious behavior, such as unusual data transfers or unauthorized access attempts, and alert security teams to potential threats in real time. AI can analyze transaction patterns in financial risk management to detect fraudulent activities or money laundering schemes, providing early warnings to prevent financial losses. In operational risk management, AI can predict equipment failures in manufacturing, allowing for timely maintenance and reducing downtime.

AI helps improve and streamline regulatory compliance processes to mitigate compliance issues. AI systems can review regulatory documents, guidelines, and compliance reports, identifying relevant regulations and ensuring business practices align with legal requirements.

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Wrapping up


Businesses recognize AI's pivotal role in driving operational excellence and sustainable growth. By integrating AI into critical business functions, organizations are positioning themselves for success in the dynamic and rapidly evolving market landscape.

Discover how global leaders harness AI and technology's power to achieve sustainable business transformation.

Accelerate your path to sustainability with the transformative power of AI. Learn more with UST Alpha AI.