Embrace Disruption: Five AI Use Cases to Support Your 2024 Revenue Growth Plan

Utilizing AI to Enhance People and Processes

Nearly all companies have had to navigate at least one significant market disruption. At the turn of the millennium, executives endured the dotcom crash, which decimated the technology landscape and inspired important business model innovations. The 2008 financial crisis upturned the relationship between companies and regulators, forcing executives to endure and plan for a new level of financial scrutiny. The rise of e-commerce forever changed the relationship between companies and their customers, elevating Marketing and Service to a level of influence previously only held by sales teams. The COVID-19 pandemic accelerated the transition to new go-to-market model sales and further embedded self-service buying as a standard solution for certain customer groups. Now, commercial executives must confront the sudden emergence of another powerful disruptor: Artificial Intelligence (AI). With the popularization of generative AI in late 2022, executives are racing to understand how this technology will change the future of how we work, including how commercial jobs will evolve to leverage AI for productivity and efficiency.

Each disruption pushes leaders to re-evaluate business fundamentals: people, processes and tools. At its core, artificial intelligence is a suite of tools designed to enable people in a way that necessarily alters existing processes. These tools aim to simplify and streamline jobs, enable better communication across people and systems, improve performance planning and measurement, and allow businesses to access new and existing customers in a scalable yet deeply personalized way.

The universe of possible AI investments is so vast and intimidating that many commercial leaders struggle with where to begin. To take the necessary first step forward, organizations should anchor investment AI decisions to top commercial growth strategies. For example, if your organization’s desired growth strategy is to unlock more total addressable market, you can invest in AI to enable lead generation teams. If your organization is looking to make sellers more productive by increasing their engaged sales time, consider AI sales assistants and coaching tools.

To illustrate, below are five commercial AI use cases powering common commercial growth strategies where companies are already realizing tangible results.

Create an AI-Enabled Lead Generation Engine

AI tools already help marketers and sellers accomplish essential lead generation functions, including generating prioritized lead lists and hyper-personalizing outreach at scale.

AI can quickly scrape and analyze data from many sources, including CRM systems, LinkedIn profiles and industry news to generate intent-rich lead lists for your next campaign. At the same time, certain tools gather detailed qualitative information about the target audience, guiding the hand of marketers and sellers to generate specific and engaging outreach language for every type of lead. AI can recommend subject lines for emails to improve open rates, craft personalized icebreakers based on company descriptions and role information, suggest how a prospect could benefit from a product or service, and even edit or enhance the tone of outreach depending on the customer profile. AI empowers marketers and sales reps alike to increase the quantity and quality of leads, improve conversion rates and more efficiently target large enterprise buyers.

Maximize Engaged Selling Time with AI Sales Assistants

According to Alexander Group’s Sales Time Benchmarking database, primary sellers only spend 20-30% of their time in engaged selling activities. Primary sellers dedicate the majority of their time to pre-sales activities (e.g., prospecting), sales completion activities (e.g., order entry) and sales facilitation (e.g., admin and reporting).

AI can dramatically shift seller time profiles away from tedious non-sales activities and allow them to spend more time selling. AI “personal assistants” help sellers optimize their time by minimizing routine administrative tasks such as pushing updates to CRM, transcribing meeting notes and even generating detailed reports on the buyer. For an additional personalization touch, certain AI tools meld task lists with buyer personality analyses, suggesting adjustments to the cadence and tone of seller interactions to generate favorable conversations with the prospect.

Create Superstar Sellers at Scale with AI-Driven Real-Time Coaching

AI can be a powerful talent and performance management sidekick, enhancing existing seller capabilities while driving down new seller ramp times, ultimately increasing close rates more efficiently.

More and more B2B sales conversations occur in recordable environments (web conferencing, phone calls), and AI tools make each conversation an active learning experience. AI analyzes transcripts, body language and tone to help sellers identify what tactics are landing with their buyers and what may have cost them a sale. Some tools proactively coach sellers on what tone to take in an upcoming sales call based on an algorithm trained by previous conversations.

AI is also a powerful tool for sales managers, enabling coaches to understand the strengths and weaknesses of their team, helping recognize and reward progress, and identifying where to put additional proactive coaching time. Some AI tools can identify and share recordings of conversations that have led to positive outcomes with the sales team, allowing teams to build a library of “best practices.” Other tools personalize training sequences for new sellers, enabling faster ramp times.

Boost Customer Experience through AI-Powered Service Interactions

According to recent research conducted by the Alexander Group, companies that intentionally invest in customer experience show higher and more profitable revenue growth. While the “customer experience” extends beyond customer service, great post-sales interactions drive repeatable sales.

Good customer service involves resolving problems proactively and efficiently. When these problems arise, customers want answers quickly, but staffing constraints can limit the availability of human agents. With recent advancements in AI, the nature of chatbots has dramatically changed, enabling these systems to have more natural and engaging conversations with customers. By implementing AI-powered chatbots, companies can now employ an automated around-the-clock service rep to enhance customer interactions, streamline processes and provide personalized experiences. In addition to constant service coverage, these chatbots also enable service agents to provide better, faster customer support by resolving common issues, providing self-service options and escalating complex cases to hand off to human agents.

Empower RevOps with Clean, Unified and Enriched Data

Data powers Revenue Operations, impacting everything from day-to-day activities to major strategic decisions. The success of this team, and therefore the commercial organization at large, depends on clean, accurate and consistent data. In reality, human errors, outdated information and unstructured sources often compromise data quality. These issues result in inaccurate insights, missed opportunities, wasted resources and poor customer relationships.

Automating time-consuming data-cleaning and data-enriching activities with AI tools can enhance data quantity, quality and organization. Many AI tools can connect seamlessly to CRM systems to automate data entry and continually check and replace out-of-date or incorrect data. AI can derive insights and data points by scanning through text files (investor reports, call recordings, webinar transcripts, emails, etc.) to extract valuable information such as planned investment areas, moves into new geographies and staffing changes. Additionally, AI can conduct targeted web scraping to find, integrate and even synthesize external data sources into helpful findings for revenue operations leaders’ strategic decisions.

Concluding Thoughts

AI is a major disruptor in the go-to-market landscape; arguably one of the biggest disruptors we’ve seen in many years. Companies invested in AI for commercial growth are beginning to see real results, though it remains to be seen where companies will generate the largest ROI from commercial organization AI investments. The use cases listed above are only five (of many) ways these tools can enable your commercial organization.

As they look at current and potential AI investments, leaders should focus on technologies that enable existing growth strategies and customer-facing roles. While AI may forever change the way that organizations work with customers, the core of the go-to-market organization will remain rooted in people and processes for the foreseeable future, thus underscoring the importance of having the right job roles aligned to the right opportunities for growth.