The ANA Global CMO Growth Council Generative AI Pulse Check
Generative AI has captured outsized attention from investors and enterprise leaders — so much so that IBM expects to see a 4X increase in Gen-AI investment between 2023 and 2025. With marketing poised to be one of the most active early adopters, CMOs are on the front lines of leveraging the technology and proving value for the entire enterprise. To help CMOs ensure their GenAI investments produce measurable gains, the ANA Global CMO Growth Council surveyed its delegates to understand how they are approaching GenAI.
This report provides initial observations from the Growth Council survey of 1,200 delegates.
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Source
"The ANA Global CMO Growth Council Generative AI Pulse Check." ANA Global CMO Growth Council, November 2023.
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SAGAR GANAPANENI
June 1, 2024 10:04pm ET
Navigating the AI Hype Cycle: Balancing Innovation with Realism:
Artificial Intelligence (AI) has captured the imagination of the world, spurring both excitement and skepticism. The cycle of hype surrounding AI often leads to misconceptions, but it is a necessary phase in understanding and integrating this transformative technology. The key is to move beyond the initial excitement and evaluate AI's true potential and limitations critically. By balancing enthusiasm with caution, we can harness AI's capabilities while maintaining trust and integrity.
Understanding Generative AI Beyond the Hype:
Generative AI, in particular, has generated considerable buzz. Its ability to create content, predict outcomes, and automate tasks presents immense possibilities. However, we must scrutinize these potentials alongside their drawbacks. Evaluating generative AI involves understanding its limitations and the ethical implications of its deployment. Striking the right balance between innovative AI applications and traditional models is essential to developing reliable, ethical AI solutions.
AI in Application and Development: A Dual Perspective:
At the enterprise level, AI's impact can be viewed from two angles: its application and its development.
Applications of AI generally fall into two categories:
1. Customer Experience Enhancement: AI fundamentally transforms customer interactions with products. For instance, digital assistants can guide users through complex processes, recommend workflows, and automate repetitive tasks, thereby enhancing user satisfaction and engagement.
2. Employee Productivity and Efficiency: Internally, AI drives productivity by aiding in knowledge management, content creation, code development, and data analysis. Tools like AI-assisted code development and data analysis significantly boost productivity, enabling quick data discovery and visualization, which empowers employees to focus on more strategic tasks.
Development of AI is increasingly becoming a core part of business strategy rather than an isolated initiative. Companies are moving towards integrating a unified AI layer to power various outcomes, rather than relying on multiple isolated models. This approach requires cross-functional collaboration to keep pace with rapid technological advancements and avoid the pitfalls of siloed development, which often leads to adoption issues.
The AI Development Maturity Journey:
Not all companies are at the same stage of AI adoption. For many, the journey begins with identifying business use cases and assessing internal capabilities. Addressing gaps may involve purchasing solutions or partnering with software providers, often resulting in a hybrid approach. As organizations deepen their understanding of AI, they can refine current processes, innovate new data collection methods, and even discover new business models.
Embracing Cross-Functional Skills:
The transformation brought by AI extends beyond technology to the talent landscape. The future of AI and analytics demands a collaborative, interdisciplinary approach. This means blending diverse skills and perspectives, fostering a culture of continuous learning and innovation, and encouraging teams to work together across functions. Breaking down silos and combining technical skills with business insights is crucial for solving complex problems and driving innovation.
Optimism for the AI-Driven Future:
The integration of AI into business strategies, the innovative applications emerging from startups, and the ongoing discussions around ethics and sustainability mark the beginning of a new era. We are on the cusp of redefining the intersection of technology and business, and with a balanced approach, we can unlock AI's full potential responsibly and ethically. By navigating the hype cycle thoughtfully, we can build a future where AI enhances human capabilities and drives meaningful progress.