Feature
In an interview with Nate Nichols — VP of product management at Tableau who heads generative AI efforts — we explored how GenAI is poised to transform sales and marketing functions. As companies face evolving demands, Salesforce and Tableau are focused on the future, anticipating critical shifts in their markets. Reflecting on Rita McGrath’s concept of inflection points, we discussed whether this moment represents a fundamental change for Salesforce and its customers. Nichols shared how they're recognizing early warning signals and assessing the subtle yet impactful shifts in market dynamics, signaling potential new directions for the future.
What are the early wins for GenAI that will impact how sales and marketing personnel do their jobs?
Nichols was clear that GenAI is a change moment for Salesforce and Tableau. He said, “according to research from Salesforce and Tableau, the number one challenge sales leaders face when trying to use data is that it takes too long to get insights. This is even though 98% of sales leaders agree that embedded analytics improve their organization’s decision making and accelerate their organization’s work.”
For this reason, Nichols argued that “the early emergence of GenAI tools that deliver data-driven insights directly into sales and marketers’ flows of work are cutting the time it takes to dig into the deep insights that really make a difference to businesses. This enables teams to get personalized and contextual insights that help them make faster, better decisions.”
At the same time, this allows organizations to automatically detect drivers, trends, contributors and outliers for the metrics business users care about and, with generative AI, surface automated analytics in plain language — within their flow of work. The goal should be for CRM users to access personalized, contextual metrics and insights natively to support daily business decisions.
Nichols argued a consequence of this is “bringing marketing and sales teams together around common business goals and shared metrics, fostering trust because the source of the data is always consistent, regardless of which team is looking at it. This means marketing and sales can collaborate around pipe generation, quarterly commits, closed ACV and more. These metrics enable marketing to keep close tabs on business performance and drive impact by creating programs that fuel sales motions.”
With this, Nichols was clear that data needs to be AI ready as suggested by Gartner.
“Generative AI is only as good as the data, so I believe that one of the early wins for GenAI is the enterprise momentum towards modern data infrastructures and data policies that help customers leverage GenAI in an intentional and responsible manner," Nichols said. "I believe every organization can benefit from the speed and interactivity of generative AI with the confidence that their customer data stays safe and secure.”
Longer term, how does GenAI transform the work of sales and marketing personnel?
Nichols believes that there is further impact from GenAI. He said, “longer term, GenAI goes beyond predictive capabilities of AI and lifts the burden of performing time-consuming repetitive tasks off the shoulders of sales and marketing people, so they can spend more time building new and stronger customer relationships.”
As an example, he said, “imagine you’re a sales rep and you’ve just been assigned a new account. Think about the hours you spend to research an overview of that company, understand the latest company news, synthesize available data to help you get your foot in the door, figure out the right contacts and then draft an intro email or call script. Now imagine you’re a marketer and the hours it takes you to sift through data and research, brainstorm on how to create a fresh ad for a new social marketing campaign, write what you think is the perfect email pitching a prospective client and scramble to find the right balance in conversations with customers who need attention. Now dare to imagine that your CRM platform is doing all of this in seconds, giving you time to not only fine-tune that personalized content and send it sooner, but also the confidence that you’re improving operational efficiencies and fueling sales motions because you’re leveraging trusted data. That’s powerful.”
Nichols said, “GenAI combined with trusted customer data can speed all of this up. It will truly reduce the friction of going from an idea to a first draft, and, with access to data that would be difficult and time consuming to get manually, it provides an opportunity to consider new insights and ideas.”
This is like the authors for “Rewired” that argue for digital trust. They say, “digital trust means confidence that an organization protects customer data, enacts effective cybersecurity, offers trustworthy AI-powered products and services and provides transparency around AI and data usage.”
Nichols argued, “the beauty of GenAI, just like the emergence of the cloud, is that while it can be a boon for large businesses, it’s helpful for small and medium sized businesses too. Capabilities like automated, AI-generated proposals and customer communications will be able to give people even more powerful tools to provide great customer experiences, manage operating expenses and achieve sustainable growth — all benefits that companies are hoping to achieve with GenAI.”
With the current GenAI solutions, what limits most the ability to get this vision?
Tools like ChatGPT and other similar systems, Nichols said, “are extremely powerful and built on public data sources. However, to work in the enterprise, the technology must be grounded in the data available in that organization. Being able to blend public and private data together securely and responsibly and in context of the unique workflows in your company is what will enable customers to realize this vision.”
Nichols said, “it’s also important to recognize that customers don’t want to be training public data models with their private data. It is critical to have a trust layer for generative AI solutions. This approach makes the use of GenAI an infinitely more valuable and trusted experience for customers at scale.”
Locking down PII and confidential information?
In exploring both near-term and long-term strategies, it's clear that securing foundational elements is a crucial first step. However, looking ahead, the vision extends beyond mere containment. The goal is to develop more advanced solutions capable of sharing information seamlessly with individuals who possess the expertise and access necessary to process and act on this data. This shift from foundational security to intelligent data dissemination promises a more dynamic, responsive ecosystem for decision makers.
Nichols said, “companies shouldn’t move forward with any solution built on GenAI until they have created or adopted very clear policies, guardrails and guidelines on what people can or can’t do with company data and AI. Because data is at the heart of any AI. AI needs to be built on trust. As part of this, it is critical to establish a trust layer to identify and mask selected personally identifiable information (PII) and payment card industry (PCI) data in the prompts before sending them to the large language model (LLM). Data masking prevents sensitive data from exposure to the LLM and keeps sensitive CRM data safely stored inside. Once the output is generated, the trust layer goes through a series of checks against bias and toxicity. Then we track and maintain an audit trail of this entire interaction, so you know what’s been used to generate that content.”
How early were Salesforce and Tableau on GenAI and how has it impacted your product road maps?
Nichols said, “Salesforce has been investing and innovating in AI for nearly a decade, beginning with our investments in AI research in 2014. Since then, Salesforce has been an AI-first company with a goal of helping all customers and employees harness the power of AI. When it comes to generative AI, Salesforce began infusing it across its entire platform earlier last year — automatically creating content from personalized emails to auto-generated code to conversation summaries. At Tableau, we have been delivering on the potential starting in 2023 to deliver personalized and contextualized insights and natural language Q&A to users to help them make faster decisions right in the flow of work.”
How important are design partners to ensure you build the right plans and functionality with GenAI?
Nichols argued, “It’s admirable to have vision and lead the industry into the future, but if you truly don’t understand the customer, it’s impossible for you to build functionality that will help them reach their end game. Design partners have always been critical to ensuring we're building the right plans and functionality in our products, GenAI included. For instance, we worked closely with Slalom. This helped lower the barrier to customers getting started. We also have an ongoing dialogue with our community of ambassadors and visionaries to learn what problems they are trying to solve and solicit their ideas on evolving the platform to meet those needs. Last year, we implemented 31 ideas from them across 20 features, which speaks to the value of their input.”
What have you learned during this journey that would be most useful to your customers considering GenAI?
Nichols said, “We’ve found that every company is looking at GenAI to create stronger relationships with their customers, which leads to higher growth. They want employees who are faster, more efficient, more productive ... which leads to higher margins. And, in this new world of AI hallucinations and data theft, they also want to have the confidence that their data is secure and trustworthy. That is what everyone is trying to achieve right now with AI. And that is what Tableau and Salesforce are striving to deliver.”
Webinar
Oct
22
Beyond Storage: Smarter Content, Bigger Impact with DAM + AI
Discover how the DAM + AI duo makes content smarter, stronger and more accessible.
Register
Webinar
Nov
6
Fix the Content Bottleneck: Build a Better WebOps Strategy
Content stalled? Dev overloaded? You’re not the only one. Learn how streamlined WebOps bridges the publishing gap.
Register
Webinar
On demand
Agentic AI Playbook: Real-World Customer Service Use Cases You Can Deploy Now
Boost self-service by 30% and slash call volume by 63% with agentic AI.
Watch Now
Webinar
On demand
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Watch Now
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Parting thoughts
Nichols emphasized the early wins of GenAI in sales and marketing, such as faster data-driven insights integrated directly into workflows, which enable sales and marketing teams to collaborate more effectively. He also discussed the long-term potential of GenAI to automate repetitive tasks, freeing up personnel to focus on building stronger customer relationships. In this process, Nichols highlighted the importance of having AI-ready data and creating trusted AI environments. Here private and public data can be blended securely. Lastly, he underscored the need for clear data policies and the involvement of design partners to ensure GenAI solutions align with customer needs while maintaining data trust and security
