By: Paul Kersey, Chief Technology Officer at Apisero, Part of NTT DATA
The competition to leverage generative AI is becoming increasingly intense, and for good reason. It has enormous potential to upgrade core business practices so you can better serve your customers — from marketing to sales and everything in between.
It’s widely accepted that the key to unlocking AI’s potential is excellent data. Better data = better AI = better customer experiences. If generative AI is a powerful new space rocket that can take businesses further and faster than ever before, then the fuel for the space rocket is data. The challenge is that improving data is easier said than done.
In this article, we’ll explore three ways that MuleSoft and Salesforce Data Cloud can help you overcome that challenge and maximize your return on investment in AI by upgrading and protecting the quality of your data.
Keeping up with competitors
Many talented people in the world of programming and IT are proponents of do-it-yourself problem-solving. And while it’s possible to manually integrate, collect, and clean up the data you need to feed into AI, it’s also a cumbersome process with data lakes, warehouses, and business intelligence tools. Most organizations can’t afford that kind of time — not just because of the additional resources needed, but also because allowing competitors to bring AI capabilities to market faster than you risks losing competitive advantage.
By dramatically streamlining the process of integrating and curating data from every corner of your organization, MuleSoft and Data Cloud can reduce both your IT workload and time-to-market for new AI capabilities.
The power of unified data
The number one obstacle we see organizations facing in their AI journey is fragmented data. When your customer, engagement, and supplementary data is spread across dozens (or even hundreds) of applications, it’s critical to bring everything together in order to get accurate and valuable output from AI.
Imagine working for a marketing team tasked with promoting the company’s latest product. While the product team is certainly excited, how can the marketing team identify a customer base that would share that same opinion? Without integrated customer information, modeling audience segments based on behavioral data that’s scattered across multiple systems is a cumbersome and time-consuming task.
Now imagine the same task but with integrated data and unified profiles. With Einstein AI, the team can now automatically identify and create those segments with generated content that is personalized based on customer activity, purchase history, and contact preferences. This not only ensures the team has reached the proper audience, but also provides a unique and personalized experience to those customers.
When you combine Data Cloud — with its built-in modeling, security, and organization— with MuleSoft, which connects your legacy interfaces, standard protocols, and APIs to feed all of your spread-out data into Data Cloud, you end up with a unified data ecosystem that can dramatically improve the performance of generative AI.
It’s important to remember that the value of unified data goes well beyond your return on investment in AI. It also improves visibility, security, forecasting, and customer insights so you can make informed, strategic decisions at every level of your organization.
Adapting and protecting
Companies on the path to using generative AI also face challenges in protecting and responsibly managing sensitive data, with three dynamic factors mounting pressure on this effort.
The first is compliance. Keeping track of and complying with regulations becomes an increasingly heavy lift with poor data hygiene — especially when those regulations continue to evolve in a variety of regions. Whether complying with privacy standards or reporting emissions, data visibility can help you meet and exceed customer and regulatory expectations.
The second is cybersecurity. Similar to compliance, the constantly changing landscape of cyber threats requires a high level of organization and proactivity to protect sensitive information. Manual programming and customized integrations often lead to increased vulnerabilities and make governance difficult to standardize.
The third is brand. Any failures in privacy or security can have huge consequences for your company’s credibility. Many customers in a variety of industries are worried about the potential pitfalls of generative AI. Building and retaining their trust will have a huge impact on customer loyalty.
Combined with NTT DATA’s proven expertise in privacy and security, MuleSoft and Data Cloud dramatically reduce the risks associated with AI and help future-proof sensitive data against emerging threats. Protecting your sensitive data is critical to the success of emerging AI capabilities.
All about the customer
In the end, generative AI provides limited value unless it improves customer experiences, and one of the best ways to ensure better customer experiences is to get a clear view of customer data. By quickly and safely unifying your customer information into one centralized platform, MuleSoft and Data Cloud are a powerful way to maximize your organization’s investment in generative AI. With well-integrated and highly visible data, you’ll be better positioned to meet customer expectations, exceed competitor performance, and drive long-term growth for your business.
NTT DATA has helped dozens of organizations set themselves up for future success in AI by consolidating their data with MuleSoft and the Salesforce Platform. If you’d like to learn more or are interested in partnering with us, don’t hesitate to contact our team.