Title Image Title Image
Home  >  PERSPECTIVES  >  Fostering a Culture of Adoption with AI

Blog

AI Culture Featured

Fostering a Culture of Adoption with AI

This week, Google showcased its integration of AI into all user interaction products, from search functionalities to task-performing agents. This rapid deployment is not only seamlessly weaving AI into every aspect of the general public’s lives, but also driving greater adoption and understanding of AI’s impact. As enterprises look to boost their implementation of AI, they can potentially follow a similar roadmap within their own organizations.

To reaffirm its relevance and dominance against OpenAI and Microsoft with the latest AI innovations, Google has deployed new features across Search, YouTube, Gmail and Docs. It has also introduced new products, including a lightweight AI model, new chips and so-called agents that assist users in performing tasks. Among these new features is Project Astra, an AI agent designed for conversational voice integration between the user and AI that is capable of responding to images or videos. In addition, Veo, Google’s latest and most advanced video-generation model, creates high-definition video, similar to OpenAI’s Sora. These AI features will be integrated into everyday use cases across all Google products, including a default experience in Search called AI Overviews. As described here, “this new experience in Search will provide AI summaries and answers to a user’s query based on live information from Search.”

“By focusing on one or two business challenges that AI can solve, companies can tackle these issues with minimal risk and high reward.”

By integrating AI technology into its platforms, Google is accelerating adoption and advocacy while gaining real-time insights into product usage, informing future features and product releases.

Lessons for Enterprises from Google’s Strategy

Enterprises can follow a similar path as they seek to disseminate AI across their organizations. By focusing on one or two business challenges that AI can solve, companies can tackle these issues with minimal risk and high reward. This approach fosters understanding of AI usage, acclimates teams to the technology and drives enterprise-wide adoption through strategic leadership.

As enterprises consider how to integrate AI into their culture and workforce, here are some suggestions for methodically deploying AI across the organization:

Deploy a small group to test and integrate AI into specific business use cases and workflows.

Define procedures and strategies to leverage AI, which can then be rolled out to the larger enterprise.

Foster a culture of continuous learning and adaptation to stay ahead of technological advancements and maintain a competitive edge.

Invest in AI training programs for employees and establish cross-functional teams dedicated to AI initiatives.

Observe the benefits and gather insights from AI deployments to refine strategies, leading to more targeted and impactful implementations.

In essence, the roadmap laid out by industry leaders like Google provides a valuable blueprint for enterprises aiming to leverage AI for transformative growth, adoption and sustained success.

Overcoming Barriers to Deploy AI

In this study by IBM, “Data suggests growth in enterprise adoption of AI is due to widespread deployment by early adopters, but barriers keep 40% in the exploration and experimentation phases.” The same study states, “We’re seeing that the early adopters who overcame barriers to deploy AI are making further investments, proving to me that they are already experiencing the benefits from AI. More accessible AI tools, the drive for automation of key processes, and increasing amounts of AI embedded into off-the-shelf business applications are top factors driving the expansion of AI at the enterprise level. We see organizations leveraging AI for use cases where I believe the technology can most quickly have a profound impact, like IT automation, digital labor, and customer care.”

The underlying message of this study emphasizes the importance of overcoming barriers to successful AI adoption. These barriers include limited AI skills and expertise, data complexity, ethical concerns, difficulties in integrating and scaling AI projects, and high development costs. If companies and their leadership agree to take small steps with AI and view each test as a pilot program for business improvement, they can build confidence in the platform, ultimately leading to enterprise-wide adoption.

AI is not an adversary; rather, it is a valuable ally, positively impacting culture, innovation and operational excellence.

Questions? Feel free to email me here. As always, thank you for reading.