Imagine a company where every decision, strategy, customer interaction, and routine task is augmented by AI. From predictive analytics that uncover market insights to intelligent automation streamlining operations, this AI enterprise exemplifies what a successful business should look like. Does this company exist? Not yet, but the building blocks for enabling it are already here.
To see what a day in the life of such an AI enterprise might look like, let’s travel to the year 2028 and visit Sandstone Services, a fictional 37-year-old mid-size company in Minnesota providing home maintenance services.
After years of steady sales and profit growth, the 2,300-employee company has hit a rough patch. Sandstone’s revenue grew just 3% last year and its 8% operating margin sits well below the industry benchmark. To jumpstart growth, Sandstone has expanded its product portfolio and decided to break into the more lucrative commercial real estate market.
But Sandstone needs to act fast. The firm must get to market quickly with its new offerings while at the same time boosting profitability by eliminating inefficiencies and working more collaboratively across teams. To accomplish all this, Sandstone is relying on artificial intelligence (AI) to achieve these goals.
Spot inefficiencies with AI
With a renewed focus on cost-cutting, Sandstone needed to identify inefficiencies and eliminate them throughout the company. To aid in this, the company developed a tool called Penny, an AI agent that’s automatically invited to all meetings. Always listening and analysing, it spots problems and inefficiencies that might otherwise go overlooked.
For example, it can tell you how meeting time is spent, revealing if too much time is wasted on non-essential issues and suggest ways to have more constructive meetings. It can do this by comparing meeting summaries against the company’s broader objectives. Suggestions can then be offered real-time in chat, or shared later in a synthesised summary.
Sandstone leaders hope that when inefficiencies and communication gaps are brought to light with Penny, employees will be much more likely to take action to eliminate them. In fact, it has already shown considerable promise. Employees are five times more likely to consider cost-cutting measures suggested by Penny.
Market more effectively with AI
Now that Sandstone has started to tackle costs, the next move in its transformation is finding new sources of revenue. It has a two-pronged approach. One is a new lineup of products and services for homeowners: smart home technology, sustainable living solutions like solar panels, and predictive maintenance. The other is its push into commercial real estate.
Smart home technology is just what homeowners are looking for. But Sandstone has to market it to the right customers, at the right time, and in the right way. A marketing platform with built-in AI capabilities is what Sandstone needs to spread the word, quickly and effectively, about its new products.
To start, it needs to segment its audience. Using generative AI, marketers can ask the system to identify tech-savvy homeowners between the ages of 30 and 60 who have spent a certain amount on home maintenance in the last 18 months. This enables more precise audience targeting, and helps marketing teams bring products to market faster.
Now Sandstone is ready to reach out to its targeted customers. Using predictive AI, it can optimise personalised marketing campaigns. For example, it knows which customers prefer to be contacted by text, email, or phone. What time of day is best to reach out, and how often? What kind of pitch for Sandstone’s new products works best? Is it one focused on cost savings, environmental impact, or preventative maintenance? This intelligence helps Sandstone reach the optimal customer quickly in a way that speaks to their specific needs and concerns.
AI allows marketers to then monitor campaign performance for red flags like decreasing open rates or click-through rates, and take appropriate action.
Sell more, and faster, with AI
With interested buyers lined up, now it’s up to the sales team to close deals. Generative AI for sales, when integrated into CRM, can speed up and personalise the sales process for Sandstone in a number of ways.
First, it can generate email copy tailored to products and services that customers are looking for. Sandstone reps can then prompt AI to draft solar panel prospecting emails. For peak effectiveness, the system pulls customer info from the CRM, to uncover which emails have performed well in the past.
Second, AI speeds up data analysis. Sales reps spend a lot of time generating, pulling and analysing data. Generative AI can act like a digital assistant, uncovering patterns and relationships in CRM data almost instantaneously, pointing Sandstone reps toward high-value deals most likely to close. How? Machine learning increases the accuracy of lead scoring, predicting which customers are most likely to buy based on historical data and predictive analytics.
Provide better customer service with AI
Sandstone’s new initiatives are going well. Costs are starting to come down, and sales of its new products are growing faster than expected. But customer service calls are rising in tandem. Sandstone is determined to maintain excellent customer service, but smart home technology poses unique challenges. It’s more complex than analogue. Things break and tend to be glitchy.
Customers need help walking through setup and use, raising the stakes for Sandstone’s customer service business. Sandstone understands that customers have a lot of choice in home maintenance providers. One bad experience with a smart thermostat repair during a heat wave is enough for many customers to move onto the next service provider.
Sandstone’s embedded AI-powered chatbots help deliver a unified and delightful autonomous customer service experience by showing up consistently across channels and touchpoints. Beyond answering common questions, these chatbots can greet customers, serve up knowledge articles, and send out a field technician if needed.
In the field, technicians can quickly diagnose and fix problems thanks to LLMs that live on their device. Picture this: A technician is diagnosing an onsite problem. Internet connectivity might be spotty or non-existent in a basement or attic, but that’s not a problem because the technician has a small language model stored on their device and instantly gets answers to their repair questions.
Check out this short demo for how your field techs can use on-device AI to diagnose and solve problems without internet connectivity.
AI is also helping Sandstone improve customer service in other ways, by analysing customer conversations and extracting relevant details. With each interaction, AI is learning more and producing more precise answers, leading to happier Sandstone customers.
Work better together with AI
Sandstone is at a pivotal moment, integrating sophisticated intelligence across sales, service, marketing, and more. That’s important, because its customers demand smooth and holistic interactions, regardless of whether they’re talking to a service rep or a sales rep.
In this new landscape, traditional departmental functions and boundaries are becoming obsolete. For example, service reps might be empowered to sell ancillary products.
Sandstone is embracing this change by ensuring that every employee is equipped with the tools and knowledge to address a wide range of customer needs. This requires breaking down silos and fostering a culture of collaboration, agility and, crucially, information sharing.
To achieve this, Sandstone has consolidated all its data into a single, accessible view for everyone in the company. Data Cloud has simplified this integration by connecting all of Sandstone’s data, no matter the source, and making it readily available to business users through the apps they use every day. This data is used to enhance LLM prompts by providing them with contextually rich information, enabling the creation of high-quality, personalised outputs.
Companies using AI: Sandstone is a model AI enterprise
Sandstone is hoping to outpace its competitors with its broad use of AI. It’s going beyond its peers, using AI not only to cut costs but to improve customer relationships, sell more, and innovate faster. That’s in line with a new KPMG survey of C-suite execs showing that revenue generation is now the primary measure of AI success, ahead of improved decision-making and productivity.
Global enterprise spending on generative AI software, hardware and services will top $151 billion by 2027, according to IDC. It sees 2024 as a “critical buildout” year as businesses make major new investments. From there, the focus will shift to investments that boost revenue and business outcomes.
Sandstone, although fictional, is already there, representing how an established company might successfully transition to become an AI-driven company.
(The Salesforce Futures team, in the latest edition of its magazine, presented three fictional companies at varying degrees of AI transformation. Sandstone is one. Check out their full analysis here.)
