According to 2023 research, most people are concerned about the implications of generative AI on data security, ethics, and bias. In fact, 81% of customers want a human to be in the loop, reviewing and validating generative AI outputs.
A mere 37% of customers trust AI’s outputs to be as accurate as those of an employee. The research found that the trust gap widens as AI goes mainstream. Brands are turning to generative AI to boost efficiency while improving customer engagement. Customers — wary of the technology risks — demand a thoughtful approach built on trust. Eighty percent of customers say it’s important for humans to validate AI’s outputs.
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Demystifying AI could significantly reduce the fear surrounding it. If we can move AI from an opaque black box to a transparent glass cube, we can recalibrate how we adopt the technology. A strong argument can be made that every AI foundational model must have a FICO score.
The latest State of IT 2023 Report by Salesforce, a survey of 4,300 IT decision makers and leaders, found that 9 out of 10 CIOs believe generative AI has gone mainstream. The report found that AI and automation underpin efficiency and innovation. Process automation is on the rise as businesses tighten their belts and seek efficiency boosts, while advances in AI prompt IT to determine how — not if — to responsibly propel their organizations forward. Eighty-six percent of IT leaders believe generative AI will have a prominent role in their organizations in the near future.
According to McKinsey, 50% of organizations used AI in 2022. IDC is forecasting global AI spend to increase a staggering 26.9% in 2023 alone. A recent survey of customer service professionals found adoption of AI had risen by 88% between 2020 and 2022.
McKinsey’s latest research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases. Generative AI will revolutionize the way we work.
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AI is the electricity of the 21st century. Ignore it and your business will be left in the dark. After all, we already know many ways that generative AI will shape how we work.
A survey suggests AI has the potential to automate 40% of the average work day, according to research firm Valoir. The widespread use of generative artificial intelligence has raised public awareness of its ability to increase productivity and efficiency, as well its risks.
So, what are the largest and most influential technology analyst firms saying about the impact of generative AI on the future of work and the enterprise? According to Gartner, generative AI will make an increasingly strong impact on enterprises over the next five years. Gartner predicts that:
- By 2024, 40% of enterprise applications will have embedded conversational AI, up from less than 5% in 2020.
- By 2025, 30% of enterprises will have implemented an AI-augmented development and testing strategy, up from 5% in 2021.
- By 2026, generative design AI will automate 60% of the design effort for new websites and mobile apps.
- By 2026, over 100 million humans will engage robocolleagues to contribute to their work.
- By 2027, nearly 15% of new applications will be automatically generated by AI without a human in the loop, which is not happening at all today.
- More than 55% of all data analysis by deep neural networks will occur at the point of capture in an edge system by 2025, up from less than 10% in 2021.
Generative AI is positioned on the Peak of Inflated Expectations on the Gartner Hype Cycle for Emerging Technologies, 2023.
IDC believes that the tech industry is at a seminal moment. Never have we seen a technology emerge with this much executive support, clearly defined business outcomes, and rapid adoption. IDC has identified three broad types of generative AI use cases that need to be assessed that are industry specific, business function and productivity related.
IDC notes that the landscape of business may be seeing a seismic shift with the rise of generative AI. IDC advises business leaders to start with the following solid foundation:
- Responsible AI policy – A well-defined AI policy that outlines principles of fairness, transparency, accountability, and data protection is paramount.
- AI strategy and roadmap and the role of the proof of concept – The AI strategy should include the rules or guidelines for generative AI proofs of concept (POCs), and it should incorporate the results of the POCs to recursively improve the strategy.
- Intelligent architecture – Data privacy, security, and intellectual property protection must also be embedded within this platform architecture.
- Reskilling and training – Most organizations do not have mature skill sets (prompt engineering, data science, data analysis, AI ethics, modeling) required to take full advantage of generative AI.
IDC also notes that data serves as the foundation for generative AI. When IDC surveyed clients about their data, troubling results were revealed.
Code generation, enterprise content management, marketing, and customer experience applications are some of the key areas for generative AI use cases in the enterprise, per IDC.
Forrester research points to the next generation of modern software development, where generative AI TuringBots speed and improve software development. Forrester defines TuringBots as: AI-powered software that augments application development and infrastructure and operations teams’ automation and semiautonomous capabilities to plan, analyze, design, code, test, deliver, and deploy while providing assistive intelligence on code, development processes, and applications.
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Forrester predicts that TuringBots will write 10% of worldwide code and tests. Here are additional Forrester generative AI predictions for the enterprise:
- One in four tech execs will report to their board on AI governance. Forrester’s data shows that 46% of data and analytics business and technology decision makers seek out partners to implement AI that’s critical to the business.
- Ten percent of Fortune 500 enterprises will generate content with AI tools.
Generative AI dominated the top 10 emerging technologies of 2023 report by Forrester. The research notes that generative AI will strain most firms’ ability to take risks and make good bets on emerging technology. Forrester research on the impact of generative AI on marketing notes the benefits of scale and precision to marketing. The research identifies the following benefits: 1. enhancing human intuition with intelligence; 2. amplifying creators’ work; and 3. adding scale and speed to creative quality.
Constellation Research believes generative AI will supercharge the future of work. The research notes that many work tasks will benefit from between a 1.3x to 5x gain in speed alone. Constellation research advice on the adoption of generative AI in the digital workplace is to have the following:
- Clear AI guidelines and policies
- Education and training
- AI governance structures
- Oversight and monitoring
- Collaboration and feedback
- Create clear ethical guidelines
- Conduct ethical impact assessments
- Monitor for AI bias
- Provide transparency
- Ensure compliance with regulations
Constellation also provides a list of the leading generative AI enterprise grade solutions. Constellation also breaks down the impact of generative AI by industry. For the education industry, Constellation notes that Generative AI, which appears to be initially loved by students and loathed by educators, is coming to education as its embedded in courseware as well as learning-management systems. The overall forecasts are optimistic, but there are cautionary notes about guardrails for AI.
Ventana Research highlights how generative AI helps sales and marketing in practical ways. Ventana notes: “For marketing, one way this will happen is by improving the efficiency of marketing copy and potentially enabling personalization at scale. For field sales, the suggestions are that generative AI will improve both the ability of sales to craft emails for outreach and responses and to enhance presentations. Other use cases include using generative AI to summarize calls automatically and post them to the associated opportunity record, improving both accuracy and timeliness. This will have positive effects on sales productivity, but on its own will represent less a revolution than an evolution.”
By 2025, more than one-quarter of sales organizations will utilize generative AI to auto-summarize meetings, personalize outreach at scale, and generate tailored sales enablement to improve sales productivity and allow more time for direct sales engagement to improve win rates, according to Ventana. The use of AI to advance automation and enhance efficiency is another example of intelligent automation as a powerful tool for CIOs.
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I will be attending the largest AI conference in the world, Salesforce Dreamforce, from September 12-14. I will meet with technology analysts from all of the institutions listed above and more, to learn more about their latest points of view on the data revolution, generative AI market trends, and use-case forecasts for the next 12-18 months. I will capture and follow up with updates on the impact of generative AI on the future of work and enterprise.