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Marketing professionals are bullish on the impact of generative AI but still investigating and learning about the effective use of the technology and safety, according to the latest research from Salesforce. 

Salesforce surveyed over 1,000 marketers representing companies of a variety of sizes and sectors in the U.S., U.K., and Australia, as part of its Generative AI Snapshot Series and found that 51% are currently using generative AI. 

Also: The impact of generative AI on software team productivity is... complicated

Generative AI-related skills and trusted first-party data are important requirements for successful generative AI adoption and usage within marketing. The importance of human oversight in the execution of generative AI in its respective roles is also a requirement given the current state of output can be inaccurate and potentially biased. 

Generating new content using AI large language models is easy work. Generating new content using AI that is on brand is hard work. 

Also: Generative AI means more productivity, and a likely retrenchment for software developers

So before diving deep into the marketing survey results, here is a reminder of what business leaders need to consider in order to take full advantage of generative AI capabilities within their organizations -- trusted data, hybrid AI foundational models that can be automated, and a single platform with security and governance built-in to ensure ethical and humane use of AI technologies. 

To unlock the power of generative AI, you need:

1. Reliable and trusted customer data to build a harmonized customer profile. Connecting clean data is critical to unlocking AI capabilities. Only with reliable and trusted data, pulled together on a single platform from service, sales, and other relevant sources, can AI even perform as intended. Remember: Good in, good out.  The amount of data generated each day continues to increase. By 2025, there will be 100 zettabytes of data in the cloud with the amount forecasted to double by 2026. To realize the full value of your data, you need to go from data collection to data that drives action by: 1. Harmonizing your data into a consistent format to create a unified customer profile, 2. Connecting your customer profile to the engagement layer your customers care about, and 3. Using your data to enable your organization to deliver great experiences.
   
2. Pre-built, custom, or public AI models -- ideally a combination of these -- to feed your data into, so insights can be leveraged into automated actions. To deliver this type of impact through automation, you need to:

• Be able to connect to all your systems -- cloud, on-premises, hybrid, or legacy -- even with the average number of apps rising (the average number in 2023 is 1,061 apps with only 26% integration).
• Activate RPA to extract data from legacy systems and assets, like docs and images, that would otherwise require manual work to access.
• Make it possible to reuse existing data and integration components, such as APIs and connectors.
• Enable the use of low- and no-code across your organization so even non-developers can participate in self-serve automation projects.

Also: Low-code platforms mean anyone can be a developer -- and maybe a data scientist, too

3. A single platform with security and governance built-in to enable both innovations and increased customer trust.  Connected, harmonized data allows you to unlock AI and automate it. The one steel thread that must be present throughout is how to enable all this securely. To establish oversight and ensure complete visibility into data governance across the enterprise, you must: 

• Have a space for your developers to work effectively without affecting production or inviting security risks, making it easy to track changes, seamlessly integrate with version control, and effectively handle release management.  
• Mask data and leverage security best practices like end-to-end data encryption to secure sensitive information (like de-identifying PII) giving your developers realistic datasets to test, without compromising security.
• Employ tools like universal API management to enable consistent data governance across systems and users.

Also: The 5 biggest risks of generative AI, according to an expert

Here are the key takeaways of the generative AI in marketing research findings: 

1. Generative AI's impact on marketing will be substantial. More than half of marketers (53%) say generative AI is a 'game-changer', and 60% of marketers say generative AI will transform their role. In fact, 51% are currently using or experimenting with generative AI at work.
2. Generative AI is transforming how marketers personalize, build, and plan campaigns. Here is how marketers are using Gen AI today -- 57% -- create groups or segments for marketing campaigns, 55% -- create marketing campaigns and journey plans, 54% -- personalize messaging content, 53% -- conduct copy testing and experimentation, and 53% -- build and optimize SEO strategy.
3. Marketers are more productive because of generative AI adoption. Marketers estimate generative AI can save them over 5 hours per week -- the equivalent of over a month per year -- to focus on more meaningful work. The survey found that: 71% believe generative AI will eliminate busy work, 71% believe generative AI will allow them to focus on more strategic work, and 70% believe generative AI will increase their productivity.
4. Generative AI skills and proficiency in marketing are low. Most marketers (66%) believe generative AI will transform the skills they need at work. Nearly half (43%) do not know how to get the most value out of generative AI. More importantly, 39% of marketers say they don't know how to safely use generative AI at work. And 34% say they don't know how to effectively use generative AI at work.
5. Content accuracy and quality are marketers' number one concern with generative AI.Here are the top marketing concerns with generative AI: Accuracy and Quality (31%), Trust (20%), Sills (19%), and Job Safety (18%). The majority of marketers (73%) believe generative AI lacks human contextual knowledge, 66% worry generative AI outputs are biased, and importantly, 76% worry generative AI introduces new security risks.
6. Human oversight, skills, and trusted customer data is a current requirement to power generative AI.The survey found that 63% of marketers say trusted customer data is important in successfully using generative AI as a marketer. The majority, 66% of marketers, also said human oversight to ensure brand voice is important in successfully using generative AI as a marketer. This means proper training is required -- 54% believe generative AI training programs are important for them to successfully use generative AI as a marketer. And lastly, 72% expect their employer to provide them with opportunities to learn how to use generative AI.

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With the trusted customer data, pre-built, custom, or public AI models that can power automation and smart workflows, a single platform with security and governance built-in to enable both innovations and increased customer trust, and proper staff training, generative AI can empower marketing organizations to deliver powerful customer experiences while driving efficiency. 

From marketing and sales to customer service and digital commerce, AI will transform the customer experience at every touchpoint. 

Artificial Intelligence

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