How Company Leaders Can Prepare For Generative AI Breakthroughs

Rapid changes in technology advancements require companies to take action. Advancements in AI technologies, including Generative AI, are the most profound change in business technology since the dawn of the commercial internet. Is your company prepared to capture the opportunity and avoid the threats?

Leaders must act quickly and not be timid in the face of rapid change. A recent Gartner survey on AI investment found that seventy percent of executive leaders indicated their organization is investigating generative AI, but only nineteen percent have graduated to pilot programs or production.  Businesses must learn new tools and ways of working to stay competitive in today's fast-paced business environment. Company leaders must embrace innovation as essential for survival and acknowledge that failure to innovate can lead to stagnation and decline.

To do this, leaders at companies of every size must champion the strategic, organizational, process, and cultural changes needed to adopt these breakthrough technologies. I’ve been fortunate to work with many of the world’s most ambitious brands throughout my 25+ year consulting career. I’ve closely observed their innovation planning and execution. The companies that embrace and implement the following recommendations are best positioned to reap the benefits of the next technology wave.

Strategic Preparedness

Start with strategic adoption. Each company has a unique opportunity to define how and where they’ll test and embrace AI technology.

Start with Clear Objectives

AI has the potential to impact many areas of your business, you will need to start by clearly defining the business objectives you want to achieve through the use of AI. This could be improving customer satisfaction, making better decisions, reducing costs, or improving productivity. Understanding the desired outcomes will guide your AI strategy.  

Identify Use Cases 

Identify specific use cases or areas within your business where AI can have a significant impact. Prioritize the use cases based on their potential value and feasibility.

Embrace Collaboration for Ideation and Business Case Building

Partner with external organizations, such as consultants, emerging tech vendors, universities, and research institutions, to share knowledge, insights, and best practices. This can lead to new ideas and opportunities for growth.

• Seek out strategic advisors with experience in embracing and incorporating new technology. When something is brand new, everyone starts with the same amount of experience in that particular technology. Look for those who can successfully navigate and integrate with your existing teams and processes.
• Look outside your own industry and comfort zone for examples of innovation done well. There are lessons to be learned in how companies succeed in the innovation process, even if the output is different.
• Seek out other companies/mentors in similar industries who have tackled similar challenges. How are they embracing these technologies? Where do they see value opportunities?

Organizational Preparedness

Embracing AI Technologies requires broad support and program commitment. 

Leadership Commitment

Leadership support and commitment is crucial for driving AI adoption. Executives must understand the risks and benefits and advocate for AI initiatives within the organization. They should allocate resources, establish clear goals, and foster a culture that embraces innovation and experimentation.

Talent and Skills Development

Building AI capabilities will require most organizations to hire or train new talent. Identify the skills needed for AI implementation, such as data science, machine learning, programming, and data engineering. Evaluate the existing talent pool and identify gaps that may require hiring, training, or partnering with external experts.

Data Infrastructure & Governance

Leaders will need to invest in the necessary infrastructure and technologies to support data storage, processing, and analysis at scale to power AI models.  This includes defining data ownership, access controls, and data management processes.  Establishing robust data governance practices to ensure data quality, security, and compliance is also an imperative.

This best positions organizations to achieve Digital Flow. Digital Flow enables companies to generate insights continuously from data produced by the brand’s digital experiences, and then applies these insights to create new, more personalized and effective digital experiences. Building this capability is a key catalyst and enabler for helping companies achieve category leadership.   

Supporting Innovation Community Building

AI implementation typically requires collaboration across different departments and functions within the organization. Breaking down silos and encouraging cross-functional teams can facilitate knowledge sharing, alignment of objectives, and effective utilization of resources. Leading organizations support innovation communities that draw from across business lines and matrixed departments. This can be done without a wholescale reorganization. Examples include:

• Launch an Innovation Lab program where selected cross-discipline experts come together to create AI pilot programs and can experiment freely to solve business problems with new technologies.
• Create a company-wide Hackathon program where all team members can learn new ways to collaborate and ideate. 
• Support optimization teams who continually test new product features and user experience treatments backed by data and automation.

Process Preparedness

New technologies necessitate new policies and processes for organizational readiness..

Establish Guardrails and Share Best Practices

While experimentation is key, leaders must manage risk and foster information sharing to accelerate learning. Examples include:

• Work with IT and legal teams to fully understand risks and opportunities. 
• Ensure that ethical and responsible AI practices are integrated into the organization's AI initiatives. 
• Establish guidelines for data privacy, bias mitigation, transparency, and fairness in AI algorithms and decision-making processes.
• Provide forums for information sharing across departments and internal learning communities.

Set Goals & Measure Against Them

Define appropriate metrics to measure the success and impact of AI initiatives. Monitor key performance indicators aligned with business objectives, such as cost savings, revenue growth, customer satisfaction, or operational efficiency. 

Regularly evaluate and report on the progress of AI projects. This will help assess the effectiveness of your innovation efforts and guide future investments and resource allocation. 

Cultural Preparedness

Leaders must create and provide company cultures that foster ideation, education, and experimentation.

Embrace Managed Risk Taking & Experimentation

Experimental cultures encourage new ideas, tolerate calculated risk taking and reward those who create breakthroughs. To do this your culture needs to encourage employees at all levels to think creatively, be unafraid to challenge the status quo and continually test and learn. This will not happen unless leadership creates a safe environment where employees feel comfortable taking risks and experimenting. Encourage a mindset that views failures as opportunities for learning and improvement rather than solely as a setback. 

Encourage Continuous Learning

Provide employees with opportunities for skill development, training, and professional growth. This can help them stay up-to-date with the latest industry trends and technologies.

• Evaluate your professional development programs to encourage cross-functional learning and empower team members to become experts in new areas.
• Empower internal experts to teach through LMS programs or informal lunch & learn sessions.
• Bring in guest speakers, case studies, or inspirational stories that can motivate and show what’s possible.

Celebrate Team Learnings

Fostering a Test & Learn mentality requires providing structured spaces to celebrate and communicate learnings. This can take place during company all-hands meetings, monthly read-outs, or during team on-sites. Empower your experimenters by asking them to present specific learnings gained from a working group and share how those learnings will be applied to a future iteration.

Focus on the Future 

A new wave of technological advancement driven by AI is dawning. The time for bold leadership is now. History tells us that some companies will adapt and innovate while others won’t move fast enough and be left behind. Companies that quickly identify the use cases where AI tech can positively influence their business and adopt the strategic, operational, process, and cultural planning steps outlined here will be best positioned to emerge as a leader in the years to come.