Invoices are processed automatically, customer interactions are personalized through self-governing AI-powered support agents, and data-driven insights inspire every business decision. AI agents are making this a reality, and the market’s projected to grow at a 45% CAGR over the next five years, underscoring the immense potential and growing necessity of these technologies.
The rapid market growth of AI agents is likely linked to the technology being a product of ‘technological leapfrogging’. This is when the speed of development in emerging markets means skipping intermediate technology stages. For example, Brazil moved directly from cash to instant digital payments, with Pix, bypassing widespread card adoption.
Regarding business technology development, many companies could jump from basic tools, like Excel, directly to AI agent automation, skipping the SaaS implementation phase. This leapfrogging creates opportunities for businesses to benefit from competitive advantages available through faster adoption of AI solutions.
So, with smart AI agents poised and ready to take businesses by storm, how do they work, what are the common misconceptions, and what are two of the biggest use cases in business? Let’s dive in.
What are AI agents (and what aren’t they)
Many businesses are perfectly positioned to leverage AI agents due to their advanced observe-plan-act cycle. This means they gather and process information from their environment and autonomously evaluate and prioritize actions based on the problem or goal. AI agents then integrate into business tools and platforms to complete their tasks. Even better, they continuously learn from past interactions, improving efficiency and effectiveness over time.
However, all new technology comes with a variety of misconceptions, and AI agents are no different.
Firstly, they’re not AI chatbots. While AI chatbots often handle customer support and simple sales transactions, they typically rely on pre-programmed responses with some natural language processing for basic understanding.
Meanwhile, AI agents perform more complex tasks, including decision-making, process automation, and workflow optimization. They use advanced AI techniques like machine learning, reinforcement learning, and predictive analytics to adapt, learn from each interaction, and make decisions without human intervention.
Still, while AI agents can act autonomously, humans at the helm will always be integral for success and AI safety, having the final say on decision-making and the strategic vision. The idea is that improvements in AI will help expand human potential and prevent time wasted on mundane, repetitive tasks. It’s not humans or AI; it’s humans and AI—companies must leverage both AI and humans in order to get the best results.
Where businesses see the biggest wins: Customer service
Salesforce data found that two out of three consumers are frustrated when customer service can’t resolve their issues instantly—likely due to AI chatbots misunderstanding the issue or human agents being offline.
Some of the most common issues customer service representatives are contacted about are order issues, billing and payment problems, and product or service support. AI agents can handle these queries as their generative AI neural pathways enable them to understand the problem, sort and prioritize queries, access customer data and business protocols in real-time, and supply the necessary information—or, if needed, escalate the query for human attention.
This enables businesses to avoid delays due to human bottlenecks, improving service speed, and enhancing customer satisfaction.
In fact, Gartner predicts that by the end of the year, 80% of customer service will be applying generative AI technology in some form to improve agent productivity and customer experience.
Where businesses see the biggest wins: Sales and lead generation
The Docusign Digital Maturity Report 2024 found that workers spend 12 hours per week on low-value tasks, which is why 21% of people said they left their jobs. When businesses are stuck wasting the time of their skilled workers on a high volume of repetitive tasks, it could be time to leverage AI agents.
For instance, if an online retailer has a member of the sales team complete the same task every day of collating sales information from the day before, manually creating a report, this isn’t a smart ROI on how the employee spends their time. And it’s unlikely to boost work satisfaction for the employee either.
However, an AI agent could integrate into the retail management system and observe the data collected from the previous day in-store and online, plan by structuring the data into a standardized report, and act by automatically creating and sharing the report.
Moreover, research also found that sales reps spent 71% of their time on non-selling tasks, making it difficult to connect with prospects. A business is built on finding and keeping customers. However, if due to being understaffed or not having a strategy in place means strong leads are slipping through your fingers, AI agents could be ideal.
It’s possible for AI agents to automate lead generation funnels with an auto-lead scoring system. This works by analyzing various prospect data points, like website visits and email interactions, and assigns lead scores based on their behavior and likelihood of conversion. Sales teams can then focus their time on prospects with the highest conversion rates, increasing efficiency and reducing costs.
Boston Consulting Group found that in one case, “A biopharma company used AI agents for lead generation, reducing cycle time by 25% and gaining 35% in time efficiency for drafting clinical study reports.”
Although AI agents may be the new kids on the block, it’s clear that they’re changing the way people do business. By implementing them as part of a comprehensive business strategy, AI agents can help employees and companies to improve efficiency and drive measurable improvements in business performance.
Article by Roberto Peñacastro, CEO and Co-Founder of Leadsales
