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Stanford Graduate School of Business (GSB) faculty, Professor Amir Goldberg, explains the urgency and opportunities of AI adoption. “The data/AI train is leaving the station. The problem is, there are many trains — and some are going off a cliff.”
The challenges of scaling AI are often not technical, but instead related to overlooked strategic considerations. But finding AI opportunities are necessary to stay ahead of the competition, Goldberg argues, “You can’t afford not to use data. Your competitors will be transforming their apparatuses into data, and they will kick you out of business.”
In order to deploy artificial intelligence technologies effectively and responsibly, executive leaders must keep learning about new AI tools and considering the business impact. Rather than pushing for automation and forcing use, leaders should take the time to strategically consider adoption.
Understanding the State of AI for Leaders
According to Stanford GSB faculty member Nicholas Bloom, AI is being adopted much more quickly than other modern technology. In a survey of 6,000 executives around the world, Bloom and his colleagues found that about three quarters of organizations use AI. The survey also revealed other trends about the current state of AI use.
- Among surveyed executives, the average use of AI was about 1.5 hours a week.
- About one-quarter of leaders did not report using AI tools at all in their work.
- Despite wide use, the expected impact of AI use is conservative. The surveyed executives predict that AI use will increase productivity by 1.4% and impact output by about 0.8%.
Although there are high rates of adoption across industries, these survey results show that many executives remain uncertain about scaling AI in their organizations. If you are considering which AI technologies to adopt and how it can fit into your existing workflows, the following questions may be helpful as you begin to make decisions about implementation.
What are your motivations for leveraging AI?
Although there are external pressures to automate processes with AI, there should also be a strong business case for doing so.
There may be a range of tools that could help you automate and optimize work for your team. But before making a plan, take time to consider your motivations and goals. Fitting AI processes into workflows that don’t make sense for your organization may lead to poor application down the line.
When making decisions about implementation, make sure you consult other members of your team and consult them on the technologies they are already leveraging in their work. Consider consulting with employees at all levels to gain insight into what processes might make the most sense to augment before developing an adoption plan.
What level of familiarity do your teams already have with AI technologies?
Your plans for scaling AI should be in response to the levels of familiarity that your team already has with emerging technologies. One way to learn more about current skills and usage is to survey the workplace about their personal and professional use of AI. This will give you a sense of what type of training would be needed, as well as a deeper understanding of sentiments related to AI adoption.
Survey results may provide insights into ideas your staff already has about implementation and learnings they have developed through their own exploration of new AI tools. By taking the time to learn about your team’s prior knowledge related to AI, you can make them active partners when it comes to new ideas for usage.
How will your team adjust workflows following planning and piloting phases?
Once you have a sense for how your team is already using AI in their work, you can begin thinking through plans for rolling out new workflows. As new tech is leveraged, it will take time to plan and pilot these tools so that they are accustomed to the best of the team’s ability. Rather than rolling out AI processes and protocols as quickly as possible, take the time to develop a thoughtful implementation plan.
The best workplace processes are those that are collaborative in nature. For this reason, it’s beneficial to select early adopters to champion AI efforts at your organization. These individuals can be key to providing feedback and giving reports about how the technologies are being deployed.
As you begin to pilot new AI use cases for your organization, remember that workflows are shaped both from the top down and the bottom up. Anyone who is affected by AI workflow changes should be able to provide feedback on the process, especially middle managers who may have a broader view into adoption.
What governance do you need to put in place before rolling out new tools?
With new professional technologies comes the need for updated rules and guidelines. AI tools can introduce specific risk to any organization. This is why leaders and other technical teams should consider risks and safety standards as fundamental components of the AI scaling process.
These suggestions may be helpful when it comes to developing AI governance at your organization:
- Document processes and contingencies to set the tone for how AI is used ethically in your workplace.
- Before large-scale implementation, make sure that you’ve considered important details relating to data security and how to protect sensitive customer information.
- Keeping the human in the loop is necessary to successful technological adoption. Be clear on review standards before rolling out workplace changes.
How will you prepare for any potential complications?
Like with all technology, AI tools will not always work perfectly and may introduce risk when it comes to your data and hardware. Preparing in advance for potential complications following adoption is crucial for scaling AI effectively.
To start, spend time with other leaders thinking through the impact of common AI errors. Consider the effects and mitigation procedures resulting from hallucination, data breeches, and information bias. Although the risk and impact will vary based on industry, every organization should spend time thinking through these potential issues.
Beyond the potential risks of adoption, many consumers may also be skeptical or concerned about these new technologies. This may also complicate your organization’s adoption. Take time to understand customer perceptions of AI use as it relates to your industry and how you’ll address this after implementation.
What are peer organizations and competitors doing in the AI space?
Although you may want your organization to be an AI leader for your industry, taking note of how other similar companies are scaling AI can provide insights into how to scale mindfully. Consider the following practices to benchmark usage:
- Stay up to date on the stances that other companies in your industry are taking towards AI.
- Call upon your professional network to begin conversations about successes and pain points related to AI usage.
- When it comes to external messaging, research successful examples of how to discuss and explain AI processes.
How Executive Education Helps Scale AI
The pace of AI-led change is moving at lightning speed, but responsible leaders take the time to consider impact before rolling out new processes. For additional support on how to scale AI in your organization, enroll in a Stanford GSB program to learn more about other topics related to implementation.
- The AI-Powered Organization (TAPO): TAPO is a one-week, in-person experience to help leaders from all industries learn how to reimagine how their organization functions with the emergence of AI. Senior executives learn how to integrate AI into their daily operations to lead with confidence.
- Harnessing AI for Breakthrough Innovation and Strategic Impact Program (AIP): Designed for senior-level executives, AIP is a one-week, in-person program that guides participants on how to leverage AI to explore opportunities and build strategic decision-making
- Digital Transformation: Leading Organizational Change in the Age of AI (DTP):
This one-week, in-person program helps senior executives to lead and implement digital transformation initiatives. The program provides a deeper understanding of the technologies, opportunities, and strategies needed to succeed.
Explore how Stanford GSB Executive Education programs can help you lead organizational change and keep on the cutting edge of AI implementation.
