Sixty-one percent of Americans believe AI could threaten civilization. 

However, 81 percent of customers prefer companies that offer a personalized experience, and 70 percent say a customized experience in which the employee knows who they are and their history (past purchases, buying patterns, support calls, and more) is important.

Based on these statistics, our very existence is at stake . . . until Amazon offers a Lightning Deal on that grill on our Wish List. 

So much for humankind. 

Whether you’re team AI or convinced the AI demons are gathering data from your toaster, everyone has interacted with AI-supported technology in some capacity, and it’s been impacting business for a long time, particularly in the financial services sector.   

“. . . The payments industry has been using predictive AI for decades, doing things like fraud prevention, customer service, anything that requires taking a very large body of data and distilling it into patterns or trends from which you can make predictive judgments,” Jodie Kelley, CEO at Electronic Transactions Association, explained.  

The innovations surrounding AI and its impact on how banking services companies operate have triggered many myths and misconceptions about Data Cloud’s capabilities. 

From concerns about job security and privacy to doubts about their practical applications, let’s debunk six of the most prevalent myths surrounding Data Cloud AI and shed light on the realities behind these powerful technologies that are transforming what customers expect and how companies deliver.  

1. Data Cloud AI eliminates the need for human intervention 

While AI can automate repetitive tasks and analyze vast amounts of data, human oversight and expertise remain crucial. 

“Artificial intelligence performs better when humans are involved in data collection, annotation, and validation. Millions of data points can be gathered by AI systems, but if the AI algorithm is not properly trained, this data is meaningless,” Afsa Ashraf said. “Data needs to be annotated by humans in order to rectify AI’s errors and expand its vocabulary. Artificial intelligence tools are significantly more powerful than humans, yet without human interaction leads, input and direction, these AI systems produce outcomes that are inconsistent or erroneous.”

From a customer-centric perspective, surveys show that 87 percent of banking customers who use chatbots and other AI-based tools prefer this technology act as support to human agents rather than replace them. 

2. Data Cloud AI is too complex for non-technical users 

Well, that’s just silly. The driving force behind Salesforce products is to simplify operations by providing central access to data and automating analytical functionality. 

Data Cloud unifies your company’s data across different systems — not just Salesforce systems. “In fact, 75% of the data in Data Cloud today comes from outside Salesforce,” Steve Fisher at Salesforce, said. “By unifying and harmonizing that data, it creates a golden record that contains all the information about your customers, your orders, cases, vehicles, or whatever entity you choose.”

Fisher added that much of the data processing could be done in real-time, which is crucial for applications such as logistics tracking, fraud detection, patient information, and customer engagement. 

“For example, we can build marketing segments by looking at how customers are engaging with our products on our website and automatically adding them in and out of the segments,” he said. 

With the proper training and support, non-technical financial services personnel can leverage AI capabilities to extract valuable insights, automate processes, and drive innovation within their organizations. 

3. Data Cloud AI poses significant security and privacy risks 

Wrong, again! While data security and privacy concerns are valid, Salesforce invests heavily in robust security measures, encryption protocols, and compliance certifications to safeguard customer data and reinforce trust. 

“The quality of customer experience is directly proportional to customers’ perception of transparency and trust,” says Prakash Thomas, Regional Vice President of Financial Services & Health, Salesforce Industries, ASEAN. “If a customer’s interaction with a business across their channels is fragmented, it is difficult to meet customer expectations. Having the right data at the right point of the customer journey helps understand their real needs and enables meeting client needs and expectations in a consistent manner.”

By adopting best practices in data management, encryption, access control, and compliance, organizations can mitigate risks and ensure the security and privacy of their data in the cloud.

4. Data Cloud AI will replace human jobs 

Instead of replacing jobs outright, AI often augments human expertise, enabling workers to focus on higher-value tasks that require creativity, critical thinking, and emotional intelligence. 

“AI is currently successful in narrow tasks while most jobs are complex combinations of many interrelated tasks that require human intelligence to carry out. However, specialized jobs also significantly benefit from AI,” said Dilmegani. “For instance, an AI application can process underwriting submissions faster than an insurance underwriter, or scan a large number of legal documents and capture relevant information faster than a lawyer.”

5. Data Cloud AI only benefits specific industries

If your business depends on customer data, intelligent GTM, more efficient operations, and a terrific customer experience—and, really, who doesn’t?—you will benefit from AI. “Business benefits of AI are hard to ignore, which reflects [in] business adoption rates,” said Cem Dilmegani at AI Multiple Research. 

Research has found that 86 percent of companies surveyed said AI is becoming a mainstream technology in their company. 

At that rate, companies that don’t develop AI strategies risk falling behind the competition in personalizing customer experiences, offering 24/7 service and targeted messaging. 

6. Data Cloud AI is a magic bullet for all problems 

AI and cloud technologies can transform many aspects of business, but they are not a one-size-fits-all solution. 

Successful implementation starts with clearly understanding organizational needs, data quality, and appropriate use cases. An experienced Business Transformation Services Team can help you align digital transformation goals with business expectations. Through careful planning and deployment, they will ensure that those expectations are realistic. 

Have questions? We can help! 

Let’s move forward with clarity and understanding, then leverage Data Cloud AI to unlock new possibilities and address the challenges financial services companies currently face with opportunities.