Our Organization’s AI: Current Status
It’s 2025, and AI is no longer knocking on our doors. It’s already in the building.
Our people use AI for a wide range of daily tasks. The demand for candidates with AI skills is growing, and AI is in itself an important tool in the recruitment process.
Meanwhile, L&D and talent leaders have moved beyond outsourcing Rote’s tasks to AI, and are now involved as strategic and creative partners. As we continue to dream bigger, our AI ambitions unfold within the larger context of organizational AI strategies and policies.
Here are some stages of recruitment to look like:
Scenario 1
Recognizing the transformational power of AI early in the game, organizations have already seen the ROI of their efforts, creating an AI ecosystem where AI and human knowledge live together and thrive.
These successful recruits are characterized as frontier companies with the latest Microsoft Work Trends Report.
All employees embody the organization’s AI strategy thanks to AI guidelines, ethics, and company-wide training on role-based AI skills and tools. In-house AI tools for all business functions are based on a shared knowledge base of technical terminology, branding language, and institutional wisdom.
Finally, organizations have a clear process of human monitoring and review to catch biases in “hastisation”, inaccuracy, and AI output, as there is an opportunity to damage organizational relationships and reputation.
These organizations are not unicorns. This level of digital transformation is within the scope of every organization. We share a few steps to creating a solid foundation that can be built for years to come.
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Scenario 2
Other organizations are leveraging AI based on more ad hoc. Certain teams utilize AI tools in specialized use cases, such as job seekers and local client inquiries. Other teams may still be looking for a compelling use case.
It is at the individual level that AI flourishes. Team members tap on the AI tool’s virtual smorgas board to take notes, summarise long reports, and generate code, images, text and other content.
We praise their initiative and curiosity!
Warning: Without organization-wide AI usage guidelines, security standards, review tools, and procedures for human monitoring and review, individual AI users will accidentally open the door to substantial risk.
These risks range from publishing content biased towards inaccurate or biased AI, to sharing sensitive information with AI tools that you “learse” and passing it on to others later.
If you feel this scenario is a little too close to your home, turn your ad hoc approach into a safe and productive AI strategy to empower your people and extend your (already powerful) internal wisdom.
Scenario 3
Still other organizations have completely banned AI. Their (understandable!) goal: protect sensitive information, intellectual property, and even personal safety.
Financial or government agencies, as well as developers of cutting-edge technology, may adopt this stance simply because there is a lot to protect.
By keeping AI off limits, these organizations have lost the potential benefits of AI and keep people behind the curve. Staff may have AI power users, but AI is treated as a responsibility and therefore they are not allowed to share superpowers.
Does that mean that everyone checks AI tools at the door? It’s unlikely.
Whether their answer to AI adoption is “still” or “never “never” or “never”, these organizations face difficult truths. The AI is already in the building.
Currently, three out of four employees bring their own AI tools to work to meet the constant demand for more, better and faster. And, unless human surveillance is consistent, they put an organization’s data security, trade secrets and reputation at risk by using ignored AI tools.
If you are trying to replace resistance with realism, a guide to responsible AI strategy can help you incorporate security and responsibility from scratch.
Common theme: AI
AI is found in all of the organizations mentioned above, but only the organizations in Scenario 1 meet it with proactive governance, implementation and usage strategies. Without this foundation, organizations face the following risks:
IP and Data Security: Without clear guidelines, using AI tools can inadvertently harm sensitive organizations and client data.
“Without guidance or clearance from the top, employees are taking things into their hands and wrapping and maintaining AI use… This approach means missing out on the benefits that can be gained from large-scale strategic AI use.
Quality Assurance (QA) and Conflict: When AI expertise is used by individuals at different levels of individuals to complete job-related tasks using different AI tools, the output is inconsistent, quality changes, and based on incomplete knowledge and context.
Duplicate effort: Without a centralized AI knowledge base that starts everyone on the same page, multiple teams or individuals will work independently on similar AI-driven tasks, leading to inefficient, overlapping efforts and output of different quality (see QA above).
Ethics and Accuracy: Due to the lack of a clear review process, teams and individuals risk and even publish AI outputs of inaccuracy, bias, or misalignment on organizational values.
Reputation and Legal Harm: AI outputs with inaccurate or biased publicly available or published AI outputs can put an organization’s reputation and legal status at risk.
Missed Opportunities: A study by Randstad found that most workers believe their company is lagging behind AI integration. Meanwhile, the World Economic Forum reports that 50% of global executives, a full 50%, cite lack of skills as the biggest barrier to AI adoption. In short, the opportunities for L&D are immeasurable.
Addressing these risks and capturing AI opportunities requires a proactive, strategic and timely approach.
We have spoken previously about how, as leaders of L&D, we are in a great position to host conversations about AI. That’s still true! But now the conversation is already underway, and many of us face efforts and bans to implement ad hoc AI, but we need to approach it differently.
As we are optimists, I believe that AI can be a force that will help us connect, create broad abundance and generally do better in the world.
We are on the edge of an era of transformation on par with the inventions of the dawn of the printing press, the Industrial Revolution, and the internet.
Think back to this extraordinary moment in human history and imagine that you can say, “I was there,” but also, “I helped make it happen.”
Let’s do this.
“We can actually make a difference in shifting the zeitgeist in this country at this moment. And then people 50, 100, 100, 1000 years later look back and say, “Oh, it’s not questionable that people found AI in that era. They’ve finally got into AI, and the AI we’ve still used for centuries.”
From Sepia to Technicolor: The current state of L&D AI
For years, we have built highly effective L&D programs and provided learners with a rich blend of modalities.
In the age of AI, we are facing major changes. The role of an L&D leader involves curating dynamic content that creates deeper, more impactful learning.
With AI, you can amplify your impact by providing learner agents, proactive research, and a truly personalized experience.
The advantage is also business. You can further increase your value by integrating AI into powerful work of learning and skills. Read on to discover four important areas.
AI Value ADD: Four Important Areas
Personalization at scale: often through the power of a custom knowledge base, adapting learning to individual needs while seamlessly connecting vast organizational knowledge. This is explored in companion articles.
Immersion and Agency: All learners are involved in freeform exploration and engagement with AI-driven 3D, immersive digital experiences in virtual reality (VR), augmented reality (AR), and mixed reality (MR).
Content Curation: Use AI-driven insights to curate relevant and impactful learning journeys.
Business Impact and ROI: Where the other three values lead: Measuring learning effectiveness and alignment of L&D strategic goals.
Under all of that, AI enables deeper organizational insights and uncovers patterns and knowledge gaps that inform important business decisions.
Discover how to unlock all of the above with L&D’s human-centric strategic framework for AI. It is designed to systematically map the AI ecosystem, amplify human potential, and help foster ethical and nuanced AI engagement across the organization.
L&D AI: Sweetrush’s human-centered strategic framework
The strategic pyramids explore in detail in three attached articles, each focusing on different levels. For now, here is a preview of what each stage has for L&D leaders, our organization, and our people.
Strategic foundation
Important AI Fundamentals: Secure Data Strategies and AI Principles, Custom Knowledge Base for Internal Knowledge and Expertise, and AI-VR Pairing across Functions.
Program enablement
Strategies in your basic AI strategy: AI skills and training and learning design and development with AI for your workforce.
Advanced modality and insights
From coaching to immersive simulation, individual AI learning experiences leverage basic assets to provide personalized solutions that impact learners.
AI Strategy: Blueprint for L&D Leaders
Are you ready to move forward with AI conversations in your organization? We have created a practical guide to help you build AI strategies from Secure Foundation to Peak implementations. AI Blueprint: Download practical strategies for L&D leaders to reduce risk, increase value, and lock the benefits of AI at scale, and begin researching digital landscapes with stakeholders, leaders and teams.
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