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A Framework for Navigating Generative Artificial Intelligence for Enterprise

Generative AI offers both opportunities and risks for enterprises. While it could drive significant ROI through personalized experiences, thought leadership, and faster processes, there are also concerns about job losses, overreliance on automation without oversight, and inaccurate information. Effective adoption of generative AI requires experience management strategies like understanding emotional and logical customer triggers, aligning products and services to experience channels, and building a business model around a compelling brand story. A people-first approach is important to maximize benefits and mitigate risks.

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A Framework for Navigating Generative Artificial Intelligence for Enterprise Platforms Processes People Product People Product Platforms Processes Sustained Momentum Stagnation Obsolescence GROWTH Strategic Inflection Points Scale Start TIME Start Scale Growth
Embracing Generative Artificial Intelligence “Artificial intelligence” isn’t new. Looking at how this technology has evolved over the years can help as you consider where and how to adopt AI in your organization. Neural Networks In 1940, John Von Neumann designed the structure of a computer that could store data and programs in its memory, while Warren Mcculloch and Walter Pitts began a deeper investigation of neural networks.. Computing Machinery and Intelligence Logic Theorist (GPS) Algorithm Governments recognized the potential of AI. In the mid-1960s, MIT professor Joseph Weizenbaum developed ELIZA, an early natural language processing program. Learning Techniques There was a lull in the 1970s and 1980s in AI research and development as governments cut off funding. Funding did not return until the mid-1990s. IBM Deep Blue & Watson In 1997, IBM Deep Blue defeated the famous Russian chess master, Garry Kasparov. In 2011, IBM’s Watson, a question-answering computer system based on Natural Language Processing, beat two former champions of Jeopardy. Source: Neil Sahota In 1950, Alan Turing asked whether machines could think like humans. He created a test, today known as the “Turing Test,” to determine the answer to this question by testing whether a computer could offer examiners solutions that would deceive them into thinking it was a human. In 1956, the first AI program, called Logic Theorist, was presented at a Dartmouth College conference, which proved mathematical theorems. The creators of the program were Allen Newell and Herbert A. Simon.
Few organizations know how to manage AI effectively. While there’s a struggle to reach top-line goals, companies are equally challenged to protect the bottom line, something generative AI can impact on both sides of the sword. Hesitation Around Generative Artificial Intelligence 100% 100% 50% ADOPTION Percentage of People Who Are Adoption: Percentages INTEREST Interest: Percentages 63% of employees expect generative AI learning opportunities from employers 63% of service professionals say technology will help them serve their customers faster.. 61% of salespeople believe generative AI will help them sell more efficiently. 84% of salespeople using AI say it helps increase sales at their organization by enhancing and speeding up customer interactions. Of service professionals currently using generative AI, 90% report it helps them serve their customers. Customer-facing roles with the highest use of generative AI include basic content creation (82%), followed by analyzing 3 4 5 48% of service providers and 39% of sales professionals fear job loss if they don’t learn how to use generative AI at work. 67% say their employer does not a generative AI training. Sales (53%) and service (60%) don’t know how to get the most value out of generative AI. 56% of employees say human oversight is critical in successfully using generative AI in their role. Only 41% of employees are currently using or planning to use generative AI. 55% of employees say enhanced security measures are critical in successfully using generative AI in
Instead of shying away from generative AI entirely, what if we shifted the conversation to innovate what’s possible with this new technology, and how to embrace those opportunities to keep your organization moving up the S Curve of Growth? ~ Jonathan Greene Co-Founder/CEO of RocketSource In
In What’s Possible With ChatGPT? ONLINE ENCYCLOPEDIAS (E.G. WIKIPEDIA) ONLINE FORUMS AND COMMUNITIES CONFERENCES AND SEMINARS JURISPRUDENCE SOCIAL MEDIA PLATFORMS SCIENTIFIC JOURNALS BOOKS AND TEXTBOOKS FILMS AND DOCUMENTARIES PODCASTS ONLINE COURSES CORPORATE WEBSITES DATABASES STATISTICS AND STUDIES ENCYCLOPEDIAS AND DICTIONARIES NEWSPAPERS AND MAGAZINES INTERVIEWS AND ARTICLES PUBLIC LIBRARIES ENCYCLOPEDIAS MUSEUMS BLOGS ARCHIVAL MATERIAL VOICE AND SPEECH GENERATION GOVERNMENT AND AGENCY WEBSITES NEWS PORTALS AND NEWS MAGAZINES TRAVEL CATALOGS AND GUIDES VIDEO GAME AI PROCESS AUTOMATION SOFTWARE DESIGN PRODUCT DESIGN SCIENTIFIC HYPOTHESIS DATA ANALYSIS CHARACTER AND STORY GENERATED DATA AUGMENTATION TEXT GENERATION STYLE TRANSFER CHATBOTS VISUAL ASSISTANTS INTERIOR DESIGN MEDIA GENERATION VISUAL WORLDS AND ENVIRONMENTS
With generative AI, humans feed the algorithm information to make decisions. The more human content we put out there, the more we feed and make it smarter. The challenge isn’t giving it enough content. It’s giving it the right content. If you treat your employees poorly, you’ll get poor results. The same is true for AI. We'll get poor results if we treat it poorly and teach it badly. You get what you put in. In It’s not the code we write to develop AI that determines their value system. It’s the information we feed them. ~ Mo Gawdat Former Google Officer The Responsibility of Working With Generative AI
Before we can have a reasonable discussion around leveraging generative AI for enterprise, we need to know something foundational — how worthwhile is it really? All signs point to us being squarely at an inflection point on the S Curve of Growth with this new technology. Trying to beat generative AI is likely a losing battle. Instead, we believe now is the time to join it, albeit strategically. In How Much ROI Can Generative AI Drive? Sustained Momentum * Personalized experiences * Thought leadership * Private knowledge database * Faster, more refined processes * More innovative experience management Stagnation * Leaning on open source AI tools * Strategy through the same lens as competitors * Low governance on ChatGPT and other generative AI tools Obsolescence * Struggle to keep up with current market demands * Struggle to remain competitive * Struggle to maintain relevance in a fast-changing environment GROWTH Strategic Inflection Points Scale Start TIME Start Scale Growth
In How Qualtrics is Leveraging Generative AI U.S. Customer Experience Management Market vs. Qualtrics Inc. Total Revenue Qualtrics remains in growth mode as they advance their technological capabilities and offer innovative solutions to their user base. Qualtrics Yearly Earnings Qualtrics Projected Yearly Earnings EFM Software Speech Analytics Text Analytics Web Analytics & Content Management Others Source: Seeking Alpha, Grand View Research, Qualtrics Billion Dollars (USD) 9 8 7 6 5 4 3 2 1 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Qualtrics is investing $500 million in AI innovation through 2027 with the goals of: ● Improving Digital Journeys ● Leveling Up Employees ● Offering Organizations Faster Access to Insights ● Enabling More Personalized Experiences ● Gather Feedback from New Places, Including Video Projected ROI Categories “AI’s ability to understand human emotion and continuously learn from experiences has the potential to make business more human, not less.” Zig Serafin Qualtrics CEO
There’s a palpable panic among team members about the possibility of losing jobs to AI. A recent Microsoft survey found that 49% of employees worry they will lose their jobs to AI. Another study by McKinsey and Company found that generative AI could absorb or automate 60% - 70%of employees’ time, meaning a distinct shift in job expectations. These statistics do not bode well for how generative AI influences experience management strategies in the workplace. In Generative AI Requires Experience Management IBM CEO among the first major executives to say they’ll replace jobs with AI Source: NY Post, CNBC, Business Insider, Euronews, Axios Nearly 80% of women’s jobs at risk from generative AI, new research finds AI to cause profound shakeup for ‘higher-wage knowledge workers,’ firm finds
AI tech layoff reports have increased as more companies navigate the murky waters ahead. In Mixed Emotions Influence the Employee Experience 84,714 36,491 37,109 17,926 14,555 10,524 9,991 *Colors represent companies that initiated layoffs Other Amazon Dell Indeed Alphabet Rivia1 Meta Salesforce Microsoft PayPal Source: TechCrunch
How the Brain Influences Experience Management The Neocortex The Limbic System is the brain’s emotional response center. It’s here that a customer is stimulated and pushed to begin his or her path-to-purchase. Tugging on the right personalized emotional triggers can serve as the spark that lights the customer’s fire and begins their journey toward buying from your business. It’s also here that a consumer returns to after a purchase is made to answer buyer’s remorse or confirm their good decision with excitement, hope, and confidence. The Neocortex houses the brain’s logic center, among other things. In a consumer's path-to-purchase, they will go through several logical stages where they consider if the product or service is relevant to them, the product will meet their expectations, it’s worth the time vs. the effort to buy, the value exceeds the cost, and the experience with the purchase will be exceptional. The Limbic System
In ● Is the business obligated to inform the customer when conversing with AI? ● How will AI approach upselling? ● What if the generative AI flies off into wonderland? ● Will customers try to trick the AI? ● How will generative AI handle hangry people? ● Could accents hinder generative AI? ● Will AI use in fast-food exacerbate obesity? ● Is AI a sentient being? Infusing Generative AI in Fast Food “The technology creates a huge opportunity for us to deliver a truly differentiated, faster, and frictionless experience for our customers and allows our employees to continue focusing on making great food and building relationships with fans.” Todd Penegor Wendy’s CEO “Generative AI is fundamentally changing how people interact with brands, and we anticipate Wendy’s integration of Google Cloud’s AI technology will set a new standard for great drive-thru experiences for the quick-service industry.” Thomas Kurian Google Cloud CEO Source: Forbes
Ethical Concerns and Bias If training data contains discriminatory patterns, generated content may reflect biases. Over Reliance on Automation Automation without human oversight can be detrimental to customer experience Loss of Competitive Edge If the workforce relies solely on AI, we’ll shift from a human economy to an AI economy. Inaccurate Information Generative AI can quickly generate content that appears authentic but is fabricated. Lack of Personalization If generative AI algorithms fail to understand individual accurately, the generated content may not resonate. Insufficient Human Touch Generative AI may lack the human touch and empathy customers often seek. Risks of Generative AI in Enterprise
Generative AI doesn’t replace a proper understanding of Product-Market Fit or product-led growth strategy for enterprise. Nuances of human behavior go far deeper than the parroted responses AI can offer. A product-led process centers on an end-user-focused growth model, where the product is the primary driver of customer acquisition and expansion. PRODUCT-LED GROWTH Source: ProductLed THE PRODUCT IS THE EXPERIENCE Loyal Customer Customer Product Team Sales Team Customer Success Team Paid Others Content Visits Sign up / Trial Marketing Team Time to Initiate Value Value Path / Realized Value PQL Generative AI Doesn’t Represent Product Led Growth PQL
Optimism Around Generative AI 17% 26% 35% 52% 60% 61% 21% 14% 40% 30% Confidence Optimism Curiosity Indifference Concern 2023 AI SENTIMENT 2018 AI SENTIMENT 2018 - 2023 AI SENTIMENT Big Tech Stock Trends Upwards NVIDIA (NVDA) META (META) MICROSOFT (MSFT) Source: Investors Business Daily
Generative AI in Gartner’s hype cycle was nearing the crest of Peak of Inflated Expectations in 2022. Many look at the emergent technology with rose-colored glasses, touting the possibilities and unsure of the risks. Generative AI will likely fall into the trough of disillusionment before we level out to where generative AI is used — the plateau of productivity. Skepticism Over the Future of Generative AI in Enterprise
In Future Legislation Could Turn the Generative AI Hype on Its Head Legislation to Preserve the Ethics of AI Intellectual Property & Innovation Liability & Accountability for AI Usage Global Regulations Increased compliance burdens can limit the availability of data for training AI models. Although critically important, bias mitigation techniques could reduce the effectiveness of AI. IP ownership concerns stemming out of AI development can hinder collaboration and innovation. Allocation of responsibility between AI developers, operators, and users could become hazy, leading to a host of accountability concerns. Cross-border regulations could muddy the waters of AI development and legislation unless a global regulatory committee is formed.
At RocketSource, we’re experts at simplifying the complex — even something as complex as generative AI — by leveraging our proprietary problem-solving StoryVesting framework. Emotional Triggers (Past, Present, Future) Logical Triggers (Past, Present, Future) Emotional Trigger (Past, Present, Future) Experience Channels Products and Services The 3 Ps The Business Story Business Model Stimulus Personalized Emotional trigger Feelings Feelings Logical Decision Making Excitement Hope Confidence Relevancy Expectations Time vs. Effort Cost vs. Value Experience A Problem-Solving Framework for Navigating Generative Artificial Intelligence for Enterprise
Emotional Triggers (Past, Present, Future) Logical Triggers (Past, Present, Future) Emotional Trigger (Past, Present, Future) Experience Channels Products and Services The 3 Ps The Business Story Business Model Stimulus Personalized Emotional trigger Feelings Feelings Logical Decision Making Excitement Hope Confidence Relevancy Expectations Time vs. Effort Cost vs. Value Experience Brand Experience: ● Getting employees and customers to buy into the organization’s “why.” ● Building a business model around the core “why” to support the passion of employees. ● Aligning the people, processes, and platforms to increase team collaboration. ● Offering products and services the customer wants. ● Placing products and services in the channels customers are most likely to access. ● Meeting experience expectations. Customer Experience ● An emotional response can be felt to the brand. ● Logical decision making around the external stimulus begins. ● The customer does a cost/effort analysis and determines if the product will meet expectations. ● The past, present, and future are reconciled into one experience that either fills the buyer with euphoria or remorse. A People-First Approach to Generative AI for Enterprise
Building the type of experiences that can withstand major disruptions, such as a pandemic or generative AI, boils down to one thing: Staying tuned in. The ability to delight customers requires that organizations get empathetic. In The Human Approach to Solving for Generative AI in Enterprise Pains Motivations Solutions Measurements Cognitive Associations Pains Motivations Solutions Measurements Cognitive Associations Cohort Cohort First-Time Buyer Employee Customer EX / CX EMPATHY MAP
Here’s the lens we use to bring new strategies and emerging ideas into a strategic focus: ● Product leads. ● The people support the product. ● The processes support the people. ● The platforms support the processes. Refining the 3Ps With Generative AI for Enterprise Platforms Processes People Product People Product Platforms Processes
Giving generative AI tedious tasks can boost productivity. ● Agents handle 13.8% more customer inquiries per hour. ● Business professionals write 59% more business documents per hour. ● Programmers code 126% more projects per week. Boost Employee Productivity by 66% by Giving Repetitive Tasks to Generative AI Data Entry Quality Control Content Management IT Ops and Maintenance Code Dev and Maintenance Accounting Hiring Process Inventory Management Document Sorting Customer Support
Checkout Free AI Experiences in Retail Source: PwC, KBV Research, RBR, Zippia, Grocery Drive 87% of retail sales happen in physical stores 80% of consumers say that speed, convenience, knowledgeable help, and friendly service are the most important elements of positive experience. AI in retail is expected to reach $24.1 billion globally by 2028. Checkout free stores live in over 20 countries worldwide.
Generative AI to Make Marketing More Efficient CONVERT Chatbots at Checkout ATTRACT Social Media Content Creation and Scheduling NURTURE Blog Post Creation ENGAGE Onboarding to Reduce Time-to-Value ADOPTER Customer Support to Answer Questions Faster ADVOCATE AI-Generated Social Prompts to Drive Word of Mouth BRAND AMBASSADOR AI Prompts for Faster Affiliate and Partner Campaign Creation LOYALIST Customer Retention Campaign Creation ATTRACT NURTURE CONVERT ENGAGE ADOPTER LOYALIST ADVOCATE BRAND AMBASSADOR
[GRAPHIC: SPOTIFY UX/UI and Generative AI Source: Business Insider, TechCrunch, Forbes “This is an incredibly fast-moving and developing space. I don’t think in my history with technology I’ve ever seen anything moving as fast as the development of AI currently is at the moment.” Daniel Ek, Spotify CEO Spotify Technology SA (NYSE:SPOT) price target increased from $140 to $160. Spotify reported 500M Monthly Active Users Over 25% of user consumption on days the DJ feature is used The feature proved so successful that it was introduced into European markets “This is an incredibly fast-moving and developing space. I don’t think in my history with technology I’ve ever seen anything moving as fast as the development of AI currently is at the moment.” Daniel Ek, Spotify CEO Spotify Technology SA (NYSE:SPOT) price target increased from $140 to $160. Spotify reported 500M Monthly Active Users Over 25% of user consumption on days the DJ feature is used The feature proved so successful that it was introduced into European markets
Generative AI and the Hollywood Strike Source: Polygon, SAG-AFTRA Committee, The Intercept, Wabe.org The opening credit scene of the Marvel show “Secret Invasion” was made completely with AI. SAG-AFTRA negotiating committee told Democracy Now! that 87 percent of the union’s members earn less than $26,000 a year. Netflix is actively hiring for a product manager of its “Machine Learning Platform” with an annual salary range of $300,000 to $900,000. Workers in tangential industries who aren’t members of SAG-AFTRA or WGA, such as makeup artists, are also hurting with productions at a halt.
Synthesia is a generative AI platform where a lifelike avatar delivers a message, training, or review to someone on the other side of the screen. These tools can be used to achieve the likeness and sound of the person sending the message. Bosch gave their teams the proverbial microphone allowed them to create professional videos using AI and share their knowledge or skill set. Leveraging Generative AI for Employee Training Source: Synthesia BOSCH AI TRAINING RESULTS USING SYNTHESIA REACH Over 30,000 views of the web-based trainings. ENGAGEMENT Over 30% increase in engagement of e-learning. COST SAVINGS Over 70% savings in external video production. USED BY OVER 500 EMPLOYEES
Outcompete But Don’t Out Sensitive Company Information Source: Washington Post, Bloomberg “Interest in generative AI platforms such as ChatGPT has been growing internally and externally. While this interest focuses on the usefulness and efficiency of these platforms, there are also growing concerns about security risks presented by generative AI.” Internal Samsung Memo Many large organizations have implemented a full ban on ChatGPT due to concerns about where and how the technology is used within their company. Many large organizations have implemented a full ban on ChatGPT due to concerns about where and how the technology is used within their company.
Bing vs. Google: A Battle Spun Up by Generative AI Source: Computer World, BofA Global Research, ZD Net, Microsoft, Similarweb Microsoft is investing $10 Billion in OpenAI in 2023 Chat GPT reached 100m users in 1/3 of the time it took Tik Tok and grew 10x faster than Instagram. One Million people on the waitlist for Microsoft’s AI-powered Bing Google’s Testing a Search Generative Experience Google search engine market share vs competitors AI-Generated Answers No link to read further or cite the source Run on ChatGBT New search experience Prometheus: a proprietary OpenAI model AI becomes the core google.com bing.com Bing and Google (main domain only) YOY change in daily visits, desktop & mobile web, worldwide
Insulate your business from disruption. Learn more at RocketSource.com/blog/Generative-Artificial-Intelligence