Generative AI: Practical Ways for Enterprises to Cut Costs and Boost Sales
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Generative AI keeps attracting more enterprise leaders. Salesforce’s Generative AI in IT Survey polled more than 500 senior IT leaders and found that 67% are making generative AI a priority in the next 18 months, with 33% citing it as a top priority.
However, they must consider the ROI before implementing generative AI in their organizations. Though we can’t calculate the exact numbers, we do know that improving ROI involves two factors: generating revenue and saving costs. Both make generative AI a valuable investment for enterprises looking to stay competitive and achieve long-term success.
Continue reading to discover how enterprise companies can use GenAI to drive revenue growth through accelerated product development, personalized customer experiences, enhanced marketing efforts, and more. Additionally, you will learn how it helps save costs by automating routine tasks, improving operational efficiency, and optimizing resource allocation.
Revenue Generation
Generative AI is set to make a big splash across industries, especially in banking, high tech, and life sciences, according to McKinsey. For instance, generative AI could add between $200 billion and $340 billion annually to the banking sector if fully implemented. The impact could be even more significant in retail and consumer packaged goods, with potential gains of $400 billion to $660 billion annually. And by 2025, Gartner expects that more than 30% of new drugs and materials will be discovered using GenAI.
Revenue Generation
Accelerated Product Development
Generative AI's potential in research and development isn't as widely recognized as its other uses, but McKinsey says it can improve productivity and save 10% to 15% on R&D costs.
Integrating GenAI into product development can decrease time to market for enterprises across industries. Generative AI excels at sifting through massive datasets, optimizing design processes, and developing fresh ideas. This improved development cycle also includes reduced testing time thanks to GenAI’s ability to generate test scenarios and synthetic data.
Generative AI can also take over the tedious tasks of creating technical documentation, design specifications, and reports, allowing engineers and designers to focus on more creative and strategic work. In addition, GenAI-powered virtual assistants can manage project schedules, track progress, and keep team communication flowing smoothly.
Personalized Customer Experiences
High customer satisfaction translates to higher sales: Cognizant discovered that industries with higher customer satisfaction grew 82% faster. Well, GenAI's personalization capabilities increase satisfaction by offering unique experiences and recommendations tailored to each customer's needs and preferences.
In addition, advanced GenAI chatbots can analyze previous interactions with specific customers and provide instant, accurate responses. This also increases customer satisfaction and frees up human agents to deal with more complex issues.
In B2C industries such as fashion, electronics, or automotive, GenAI allows for product customization, which often leads to higher prices. In service-oriented sectors, GenAI can customize offers based on customer profiles.
New Revenue Channels
Generative AI can help businesses find and develop new revenue channels through innovative product development, market expansion, better customer engagement, and streamlined operations. So, to stay competitive and profitable, it’s time to start adopting GenAI.
For product development, GenAI can help design new products by analyzing feedback, market data, and tech advancements, resulting in unique offerings that capture new segments. For instance, businesses with large datasets can explore new models like AI-as-a-Service, offering GenAI-driven solutions to other companies. It can also create new service models like subscriptions or AI-driven consultancy.
Personalized pricing is another benefit. GenAI can offer tailored prices based on customer behavior, boosting sales.
Enhanced Marketing and Sales
Gartner’s prediction that by 2025, 30% of outbound marketing messages coming from enterprises will be generated by AI is no surprise. Integrating generative AI into marketing and sales helps businesses personalize their approach and improve targeting, which leads to better customer engagement, higher satisfaction, and increased conversion rates.
As the name suggests, generative AI is great at creating marketing content, like personalized emails, social media posts, and ads at scale. GenAI can optimize SEO and content strategies by suggesting effective keywords, topics, and formats based on search trends and audience interests. This allows businesses to consistently deliver engaging content, reach more people, and increase sales.
Generative AI can also help you understand customers' feelings about a brand by analyzing feedback, reviews, and social media mentions. By monitoring sentiment, companies can make smarter decisions to boost customer satisfaction and improve their brand image.
If your company has large amounts of customer data, GenAI can analyze this information and create personalized content or campaigns for specific users or different versions of ads for various customer segments. It can also continuously monitor campaign performance and provide real-time optimization tips.
Additionally, GenAI can analyze information about sales leads and turn it into extensive profiles. With this data neatly structured and presented, sales representatives can identify and prioritize leads and find the optimal approaches to nurturing them.
Overall, McKinsey estimates that generative AI could improve marketing productivity, boosting it by 5% to 15% of total marketing spending and, based on current global sales outlay, improve sales productivity by 3% to 5%.
Cost Savings
Generative AI's cost-saving capacity comes from its potential to optimize operations and automate routine tasks. For example, McKinsey claims that GenAI can automate the work that currently takes up 60% to 70% of employees’ time.
Cost Savings
Automation of Routine Tasks
Thanks to generative AI, workers can, at least partially, unload some complex and time-consuming tasks like data analysis, marketing content creation, and customer service. For instance, with GenAI-powered chatbots handling common customer inquiries, human agents can tackle more complex issues.
Automated ticketing systems can sort and prioritize customer service tickets based on urgency, ensuring critical issues are addressed quickly without much manual effort.
GenAI can also automate data entry tasks like updating customer info, processing invoices, and managing payroll, reducing the risk of human error. In document management, GenAI can automatically organize and retrieve documents, making it easier for employees to find what they need quickly.
In finance, generative AI can handle invoice processing, ensuring timely payments and reducing the workload on the accounting team. It can also streamline expense management by automatically categorizing and approving expenses based on set rules.
In HR, GenAI can simplify recruitment by screening resumes, scheduling interviews, and even conducting initial interviews with chatbots. Additionally, GenAI can provide new hires with personalized training materials during onboarding, answer routine questions, and guide them through necessary paperwork.
For sales teams, generative AI can qualify leads by analyzing data and scoring prospects based on their likelihood to convert. This allows the team to focus on high-potential leads and work more efficiently.
Improved Operational Efficiency and Dynamic Resource Allocation
Generative AI can increase efficiency by optimizing workflows and processes in various industries. Take manufacturing or supply chain management, for example. GenAI can create optimized production schedules that cut down on waste and keep everything running smoothly.
In dynamic workforce management, generative AI can help by analyzing demand forecasts to ensure that the right number of employees are scheduled at the right times.
GenAI is also great for training. It can personalize training programs so that employees receive the most relevant and effective instruction. This approach saves time and money compared to traditional training methods and helps employees get up to speed faster.
In addition, GenAI can take over the reordering process by determining the best time to restock based on how much is being used and how long it takes to get more. This helps avoid running out of stock and keeps you from having too much inventory on hand.
Reduced Customer Support Costs
We’ve already mentioned automated ticketing and GenAI-based chatbots that are available 24/7 to answer questions about products, services, orders, and account issues. Now, let’s look at the other ways GenAI can help reduce customer support costs.
One paper studied how a generative AI-based assistant affects productivity among 5,179 customer support agents. The results showed that using the tool boosts productivity by 14% on average (measured by issues resolved per hour). Interestingly, novice and low-skilled workers see a 35% improvement, while experienced workers aren't much affected. The same study suggests that AI assistance leads to a 25% drop in customer requests to speak to a manage.
Even though human conversations seem more personal, generative AI can analyze loads of data to provide tailored support. This makes conversations more relevant and effective. GenAI can also power interactive FAQ sections that provide accurate, context-specific answers, encouraging customers to help themselves and reducing the number of support tickets.
For the support team, generative AI can offer real-time help by suggesting responses, retrieving relevant information, and guiding them through the troubleshooting steps. This increases agent productivity and reduces training costs. In addition, GenAI can analyze support data to identify common issues and their root causes or process customer feedback to identify recurring pain points, reducing repeat contacts.
Last but not least, GenAI-driven support solutions are scalable and can handle more requests without the need to increase the number of employees. GenAI can also provide support in multiple languages without needing a multilingual team.
Predictive Maintenance
Although generative AI isn't usually the primary type of AI model used for predictive maintenance, it can still contribute to this purpose. For example, GenAI can create synthetic data to supplement the training data, especially when little historical data is available. This makes predictive models more robust and accurate. Moreover, generative AI can simulate different operating conditions and possible failure scenarios.
Additionally, GenAI helps with regulatory compliance by keeping detailed records of all maintenance activities. It provides evidence of regular maintenance, helping you avoid fines associated with non-compliance. This thorough documentation ensures you meet all regulatory standards, giving you peace of mind and protecting your company from legal issues.
Cost-Effective Marketing
By now, you probably know that generative AI excels at creating personalized marketing content and targeted ad campaigns. This ensures that content is relevant and engaging and reduces the need for extensive manual content creation.
Generative AI is also great for tracking and analyzing customer interactions across different touchpoints, giving companies detailed insight into customer behavior. When companies know what their customers want, they can adapt their marketing efforts and use their budgets more effectively.
GenAI can also help with localizing products and marketing strategies, such as translating into another language, cultural adaptation, and region-specific customization, making it less costly to enter and succeed in different markets.
When it comes to testing marketing campaigns, AI makes things much easier and more cost-effective. It can automate A/B testing to quickly determine which variations work best, saving time and money compared to manual testing.
Enhanced Decision-Making
Generative AI is set to greatly impact knowledge work, especially in areas like decision-making that were challenging to automate before. Namely, McKinsey found that the potential to automate such expertise-based tasks jumped by 34% with GenAI.
Thanks to data-driven insights and simulations, GenAI reduces the risk of costly errors. And it’s not just customers who get tailored recommendations from GenAI; it can offer customized tips for data-based decision-making based on specific roles within the company.
By analyzing vast amounts of data from multiple sources, generative AI solutions give companies a clear view of trends, patterns, and correlations that may not be obvious from manual analysis. They can also run what-if scenarios, helping businesses evaluate different outcomes and choose the best strategies.
When it comes to market analysis, AI can examine market conditions, competitor activity, and consumer preferences to support strategic planning. This helps businesses spot opportunities and threats at an early stage and make proactive and cost-efficient decisions.
Talent Optimization
With generative AI covering some or all of the load of employees, there’s no need to hire more people. For example, AI can handle the initial screening of resumes and picking out candidates with the right qualifications and skills, which saves a ton of time and money compared to doing it manually.
GenAI can also create customized onboarding programs that fit each person's needs, helping them get up to speed quickly. This shortens the time it takes for new hires to become productive and cuts down on onboarding costs.
GenAI's ability to monitor employee performance by analyzing work patterns, productivity, and feedback has two advantages. First, it gives managers real-time insights into how everyone is doing and where improvements can be made. Second, it provides employees with personalized feedback and development plans based on performance data, helping them improve their skills.
A targeted approach like this is much more effective and cost-efficient than one-size-fits-all training programs.
Conclusion
Enterprises should seriously consider implementing generative AI if they want to boost revenue and cut costs. It automates routine tasks, accelerates product development, personalizes customer experiences, and optimizes marketing strategies, improving efficiency and saving money. Generative AI also improves customer support through AI-driven chatbots, reducing labor costs and optimizes talent management by automating recruitment and personalized training.
The advantages are too good to pass on, so consider improving your enterprise through GenAI today. It’s easy to do with Dynamiq's low-code platform. With pre-built modules and custom Python extensions, businesses can automate, optimize, integrate, and innovate with AI workflows, driving growth and efficiency.
