Generative Artificial Intelligence (GenAI) has gone beyond being a “nice to have” technology. GenAI is now a powerful force causing huge disruptions in the way of doing business. Businesses that do not adopt the technology will soon fade away into irrelevance.

Early adopters of GenAI will thrive and can define the rules of their industry, leaving competitors behind. CxOs who make the best use of GenAI can take the enterprise to the next level of growth.

Efficiency improvements

Artificial Intelligence (AI) has always been a strategic enabler of automation. First-generation AI tools enabled rule-based automation. GenAI enables cognitive automation. CxOs use GenAI to create systems to understand, learn, and apply intelligence across various tasks.

The algorithms analyse big data to identify patterns and trends outside the capabilities of human brains. These insights help decision-makers make data-driven decisions that optimise processes and resource allocation.

The implications are huge

GenAI bots can take over repetitive tasks such as order intake, verification, and initial processing.

In field service, GenAI analyses real-time traffic data and historical patterns to plot optimal routes. Faster and error-free delivery of goods or services boosts the customer experience.

AI taking over time-consuming tasks leaves employees with more time. They can focus on higher-level tasks related to creative problem-solving and customer management. Their productivity and motivation levels improve.  Skilled employees feel valued and will stay with the company, reducing employee churn.

CxOs can add value by prioritising use cases for GenAI-powered automation. GenAI will not know the enterprise goals, operational structure, and pain points. Such knowledge is with the CxOs. For instance, CxOs can pinpoint areas where repetitive tasks or slow decisions hinder efficiency. They can leverage such knowledge to pinpoint areas where GenAI will make maximum impact.

Improving customer service

Chatbots reduce costs for the enterprise. But they have a reputation for being inauthentic and delivering a dehumanising experience.

First-generation chatbots process only simple queries and churn out rule-based responses. They often misinterpret complex questions and fail to grasp sarcasm. They struggle with natural language and get stuck in repetitive loops.

GenAI removes these disadvantages and lends an authentic touch to automated customer experiences. GenAI-powered chatbots can engage with customers in the language and tone of their choice. It delivers context-aware experiences tailored to the customer’s specific needs and circumstances.

Also, GenAI-powered chatbots can accommodate unpredictable customer call surges. Businesses do not have to hire and train temporary workers, who may deliver poor-quality output anyway. Eliminating wait times does away with a big customer pain point.

CxOs know more about customer journeys, touchpoints, and pain points than any algorithm. They can add value by identifying areas where chatbots will provide better service and areas best left to human agents.

Enabling personalisation

Another key area of GenAI application is to deliver personalised customer experiences.

Delivering personalised experiences helps CxOs retain customer interest. This becomes very valuable today when competition is cutthroat, and customers remain spoilt for choice.

The advanced algorithms of GenAI tools become powerful tools in the hands of the CxO. They can use these tools to understand customer needs and tailor products or services to match such needs.

Consider an ecommerce storefront. A traditional screen offers generic recommendations based on the customer’s purchases or trends. GenAI tools analyse the customer’s browsing behaviour in real time. It considers factors such as the time of day, the pages the customer lingers on, previous searches and any other available cues. Based on such data, GenAI understands what the customer seeks. It recommends specific products and add-ons. Personalised real-time recommendations and offers increase upselling and cross-selling as well.

Another example is creating personalised investment portfolios with unmatched granularity.

Streamlining the supply chain

Another big area of GenAI adoption at the enterprise level is supply chain management.

AI algorithms analyse historical sales data, weather patterns, seasonality, trends, and product lifecycles. It uses such information to optimise demand forecasting and predict potential disruptions.

GenAI takes these capabilities to the next level. It considers real-time data, such as social media trends and live customer sentiment, to optimise inventory charts. It analyses live conditions to plot the best delivery or supply routes. It also automates the documentation process associated with logistics. All these save time, ensure process accuracy, and make the supply chain more resilient.

The CxO’s role goes beyond ensuring funding and implementing the GenAI tools. GenAI implementation cannot exist in a vacuum. CxOs ensure GenAI-powered applications contribute to broader business objectives. For instance, the application can prioritise reducing costs or improving on-time delivery rates. On-time delivery might matter more than costs for cargo with a short shelf life. Reduced costs might matter more for fast-selling, stable products with thin margins. The CxO has to decide on the desired course, depending on business priorities.

Better product design and development

CxOs have started to use GenAI in product design and development.

GenAI tools identify unexpected connections that humans miss. These tools churn out intuitive ideas that mimic and improve human output. 

Best-in-breed CxOs use these tools to:

• Create products or structure services that resonate with customers. 
• Refine pricing strategies and execute targeted marketing campaigns.
• Prioritise resource allocation.

For instance, the GenAI tool may identify a high-value customer segment with specific needs and develop a premium service tier. The tool also identifies the best marketing approach and generates marketing collaterals. GenAI’s ability to auto-generate content on the fly makes targeted and personalised marketing easier.

GenAI also finds widespread adoption for further innovation. GenAI tools foster a constant stream of fresh ideas. These tools also accelerate the process by auto-creating design concepts and prototypes.

The role of the CxOs here is to establish a clear vision of GenAI use or the direction in which innovation is to proceed. They have to make sure the direction aligns with business priorities. The priority could be to develop new product categories, personalisation, or optimising processes.

GenAI has the potential to drive transformational change at the enterprise level. But, to get the maximum value out of the investments, the CxOs have to:

• Break down data silos and ensure data accessibility to foster collaboration.
• Promote explainable AI (XAI), which makes the reasoning behind GenAI’s creative outputs explicit. Users will not trust the technology if the GenAI algorithms operate in a black-box mode.
• Communicate GenAI’s value proposition to stakeholders. Without clear and proactive communication, user adoption and trust will remain muted.
• Establishing systems that allow human oversight. GenAI will fail if the technology dictates terms.
• Implement data governance practices to ensure GenAI does not lead to data privacy or security concerns.

Two out of three enterprises have already started using GenAI, suggesting an imminent technology race to outsmart competition. GenAI can become a powerful beast that unlocks competitive advantages for the enterprise. But only for those enterprises where CxOs know how to extract value from it.