Editorial
The Gist
- Tech foundation. Building a unified data architecture is crucial to harness AI’s full potential.
- AI factory. Establishing an AI factory streamlines the transition from idea to implementation.
- Strategic investment. Investing in leadership and technology is essential for maximizing AI’s ROI and impact.
With artificial intelligence reshaping industries at breakneck speed, the question for most organizations is no longer: "Should we adopt AI?" Instead, it’s: "How do we become an organization leading in AI?"
The urgency is clear: according to McKinsey, 72% of organizations have adopted AI in at least one business function. Yet, despite widespread recognition of AI's potential, many leaders find themselves grappling with the complexities of implementation.
The gap between acknowledging AI's capabilities and successfully integrating it into organizational DNA is fraught with challenges. How do you move beyond pilot projects and sporadic applications to truly embed AI into the fabric of your company? How can you ensure that AI initiatives align with your strategic goals and deliver tangible value? How do you open capacity with AI and use that capacity to drive innovation?
4 Steps to Becoming an AI-First Organization
My team developed a four-point plan to help organizations navigate this transformation successfully. This roadmap is about fundamentally transforming how a company thinks, operates and makes decisions to ensure success in the age of AI.
1. Build the Tech Foundation
The journey to becoming an AI-first organization begins with building a solid technological foundation. This crucial first step involves consolidating data from various systems into a single, unified platform — because AI is only as powerful as the platform it is built on and the data it has access to.
Consider this: the average large company has more than 80 employee-facing systems, each representing a potential data silo. To harness the full power of AI, these silos must be dismantled.
Creating a unified data strategy is essential. Say the words “data architecture,” and most CHROs shut down. That needs to change. Historically, CHROs would delegate these decisions to their IT or HR tech leaders, but it's important for CHROs to understand the implications of these decisions. Think strategically about the problems you're trying to solve and ensure you have the right data in the correct place to solve them. This is the fuel that will power your AI initiatives across the organization.
Take, for example, the onboarding process. To create an exceptional AI-driven onboarding experience, you need to pull data from IT, legal, HR and learning experience platforms. For most organizations, this data is distributed across various systems and functions. The key is bringing all this information together to power AI-driven recommendations and streamline the onboarding process.
By focusing on building the tech and data foundation first, you're setting the stage for more advanced AI applications down the line and creating an ecosystem where AI can thrive and deliver value across multiple touchpoints in your organization.
Related Article: Businesses Learn What AI Can Actually Do
2. Create an ‘AI Factory’
Once you have your data foundation in place, the next step is to establish what I call an "AI Factory," an operating model that efficiently moves ideas from conception to implementation. It's a cross-functional effort that involves various departments and stakeholders.
The AI Factory starts with idea intake. Every role in your organization likely has insights on how AI could improve their job. Establish a system for collecting these AI-related ideas from across the company. This could be through regular brainstorming sessions, a dedicated digital platform or even AI-powered suggestion systems.
Next comes prioritization. Develop a process for evaluating and prioritizing these ideas based on potential impact and feasibility. This is where having a clear AI strategy aligned with your overall business goals becomes crucial.
The key to an effective AI Factory is streamlined governance. Create efficient pathways for ideas to move through necessary checks and balances without excessive red tape. This includes involving (as needed):
- Legal teams
- IT
- Data security teams
- Data privacy teams
- HR
The goal is to maintain proper oversight to ensure moral, ethical and legal use of AI without stifling innovation and speed.
Finally, ensure that prioritized ideas reach the teams capable of building them as quickly as possible. This might involve creating dedicated AI development teams or upskilling existing tech teams to handle AI projects.
The AI Factory approach helps organizations focus on AI use cases that align with their strategy and principles while maintaining agility and speed in implementation, creating a repeatable, scalable process for turning AI concepts into reality.
3. Invest Strategically
To accelerate AI adoption and maximize its impact, organizations need to make strategic investments that align with organizational goals. I believe and have seen the amazing ROI AI solutions can have, but all of them require up-front investment.
Start by investing in leadership. This is not a side job or something that can be distributed across many employees with minimal time commitment. Consider hiring a dedicated AI leader for HR who can devote 100% of their efforts to thinking through AI implementation. This person should have a deep understanding of both AI capabilities and your organization's unique needs and challenges.
Next, focus on data quality and governance. Implement processes and tools to ensure data accuracy, consistency and compliance with relevant regulations. This might involve hiring data quality and governance specialists. Someone needs to be responsible for data quality, which is not true in many HR organizations today.
Only after you've invested in leadership and data quality should you turn your attention to AI infrastructure and tools. This might include data management systems, AI development platforms or integration capabilities. The key is to choose technologies that align with your AI strategy and can scale as your initiatives grow.
Finally, develop metrics and systems to measure the ROI of your AI initiatives. This will help justify further investments and guide future strategy. Measure time savings and convert that to dollar value, and ensure you share the findings with key decision makers. Remember, becoming an AI-first organization is a journey, and your investment strategy should evolve as you progress and demonstrate value.
Related Article: 6 Considerations for an AI Governance Strategy
4. Enable and Educate
As AI transforms the workplace, supporting your workforce through this transition is crucial.
Begin by conducting an assessment to identify tasks best suited for AI augmentation in your organization. Map those tasks to roles to identify where in the organization AI is likely to create capacity. We call this an AI Heatmap and use it to inform targeted upskilling, which helps to prioritize areas for employee training.
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Next, develop an AI enablement strategy. We focus on three pillars:
- Know AI: Ensure all employees have a foundational understanding of AI, such as prompt engineering and identifying use cases.
- Use AI: Provide training for those using AI tools, helping them understand both their capabilities and limitations.
- Build AI: Upskill technical teams, including engineers and data scientists, to create and implement AI-driven solutions.
It’s also important to foster a culture of continuous learning and adaptation. As AI capabilities evolve, ensure your workforce stays up-to-date with the latest developments and best practices. This might involve creating internal AI education programs, partnering with educational institutions or leveraging online learning platforms.
Finally, implement change management strategies to ensure employees understand AI’s impact and the opportunities it creates for growth. Transparency is key — help employees see how AI will enhance their roles, remove mundane tasks and further their career opportunities.
From Strategy to Action: Moving Forward With AI
By focusing on these four pillars — building the tech foundation, creating an AI factory, investing strategically and enabling and educating your workforce — organizations can successfully transition to an AI-first approach. Those who harness AI as a fundamental part of their organizational DNA will gain a significant competitive advantage.
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