Preparing Your Organization to Navigate the AI Revolution

By Colleen Campbell, Founder and AI Strategist

We are standing at the threshold of a new renaissance, where technology and human ingenuity converge to rewrite the rules of business. The expectations are bold: AI's global economic contribution will reach $15.7 trillion by 2030 and 72% of leaders now recognize AI as a competitive edge.[1] [2] These aren't just statistics – they're predictors of a fundamental shift in how we work, create, and innovate.  Our business will be the same but how we work will change.  With AI-enabled companies reporting 20-65% higher productivity, the question isn't whether to embrace AI, but how to harness its potential while amplifying, not replacing, human capabilities.

So regardless of where you are on AI journey, we will explore AI’s current progress, what’s coming next and how you need to prepare your organization.

AI Current State

While only 13% of companies globally feel prepared to fully embrace AI's potential, this gap represents not just a challenge, but a call to action for leaders.[3]  The stakes are clear - competitive viability in a rapidly evolving marketplace; operational excellence and risk management; and workforce evolution and empowerment.  Many leading organizations are embracing this opportunity:

• Healthcare: At Mayo Clinic, AI is supporting doctors and nurses to analyze complex medical imaging with 99% accuracy, allowing physicians to focus on patient care and treatment strategies. Radiologists now spend more time interpreting complex cases and providing care, while AI handles routine screening and pattern recognition. This can lead to faster diagnoses, more personalized treatments, and more focus on the human medical connection.
• Financial Services: JPMorgan Chase’s COiN (Contract Intelligence) platform processes legal documents in seconds. This task previously consumed 360,000 hours of human time annually. Lawyers can now focus on complex negotiations and client relationships, while AI handles documentation and initial analysis.
• Manufacturing: Siemens’ predictive maintenance systems use machine learning to anticipate equipment failures before they occur, reducing downtime by up to 45%. Workers move from reactive maintenance teams to proactive solutions, using AI-generated insights to optimize entire production systems.
• Retail Sales: Nike's digital platforms use AI to design personalized product recommendations, create custom shoes, and even predict emerging fashion trends. The technology doesn't replace the creative designers but empowers them to understand customer desires with unprecedented depth and precision.

What’s Coming Fast with AI

It’s understandable why organizations are confused where to invest and how to implement AI. Not only do you need to understand some of the low hanging fruit, such as document scanning and basic predictive modeling, but AI is changing so quickly that even the experts struggle to learn the latest.  Below are a few emerging and prominent AI technologies for 2025.

AI Agents

AI agents are being implemented rapidly to become a key part of the AI revolution in the simplest terms. In the simplest terms, they are given a key task, autonomously seek a resolution and return with an answer or complete a task.  AI agents automate routine tasks such as scheduling your meetings, automating data entry, and generating reports to review with your morning coffee.  This allows employees to focus on more strategic activities. Multi-agent systems (MASs) bring together multiple agents to work together as one team to streamline complex workflows by coordinating between different systems and processes, ensuring seamless operations.  Large SaaS platforms such as ServiceNow are building agents into their workflows to automate basic tasks like IT ticket prioritization and resolution.  Below is an example on how a group of agents and human automate a marketing campaign.

In the example above, various agents are engaged to create and manage specific tasks and the human is constantly in the loop to request changes as needed and approve.  The Central Process Manager Agent facilitates the full process which takes hours off the marketing campaign creation.  By incorporating human reviews, the campaign can maintain quality and relevance, ultimately leading to more successful marketing outcomes.

Agents will revolutionize how we work.  Here are some agent uses.

• Predictive Analytics: AI agents analyze large datasets to forecast trends, helping businesses make informed decisions.
• Real-Time Monitoring: They provide continuous monitoring of business metrics, alerting stakeholders to anomalies or opportunities promptly.
• Recruitment Assistance: AI agents screen resumes, schedule interviews, and even conduct initial assessments, streamlining the hiring process.
• Employee Engagement: They facilitate onboarding, training, and provide support resources, enhancing the overall employee experience.

Geospatial Recognition and Augmented Reality

I recently listened to The TED AI Show on geospatial recognition with Niantic’s Brian McClendon.  Do you remember when finding imaginary Pokémon was all the rage back in 2016? I was one of those moms schlepping my child around to chase those invisibles creatures.  This is back in vogue with geoguessers identifying locations around the world sometimes in just a few minutes.  This bottoms-up location recognition is a community-based contribution to spatial data.  This provides a wealth of evolving geospatial location information as our world changes verses completely leaning on satellite.

From a use case perspective, this could help with national security, understanding climate change, resource allocation, supply chain management and augmented entertainment opportunities.  Imagine hiking a trail looking through Meta’s Orion glasses viewing a mixture of virtual and augmented reality. Maybe you envision a field during a battle hundreds of years ago or you scan a flower and learn more about that specimen.  It may eventually be hard to tell actual from virtual as this augmented reality evolves.

AI Robotics

As I craft this article, I can hear my Roomba running upstairs.  Physical AI which includes machines like robots and self-driving cars have advanced greatly over the last year.  Robotics have struggled with mastering human physical agility but that is changing quickly.  AI learning in virtual worlds that obeys the laws of physics has increased the agility ability.  We will see more robots in plants, warehouses, in our homes and out on the streets.  Here’s a Nvidia video on this transformation.

So How Do I Prepare My Organization

These are interesting times.  Reimagining your organization as a living, breathing ecosystem where artificial intelligence acts as a powerful catalyst and partner that transforms how we work, innovate, and create value is daunting. It’s scary, exciting, hard and unclear, but it is the future.  Taking that leap of faith is required to truly stay competitive and effectively prepare your customers and employees. Companies that ignore AI will fall behind in innovation, efficiency, security, and revenue growth.

The most successful organizations are viewing AI not as a technical upgrade, but as a strategic partner in human achievement. They're asking:

• How do we preserve our unique strengths while embracing AI's capabilities?
• Where can AI free our teams to focus on strategic thinking and creativity?
• What does leadership look like in an AI-augmented workplace?

Let’s explore each of these questions.

1. How do we preserve our unique strengths while embracing AI's capabilities?

AI won’t change who you are as a business, but it will change how you run your business. To navigate this transformation, start by embedding an AI Center of Excellence to guide your AI evolution.  This should include an enterprise and product-level AI strategy, governance, product adoption, and workforce model.  Together this sets the direction, priorities, risk management and engagement needed to achieve AI success.

These AI structures protect and enhance your core capabilities. For example, if your corporate strengths are exceptional customer service and reliability:

• AI strategy should state customer satisfaction and reliability in your AI vision and prioritize AI products to amplify this strength
• AI portfolio KPIs measure how these products improve, protect or drive customer satisfaction and reliability
• AI governance provides the ongoing structure to ensure customer satisfaction and reliability is increased due to AI and that risks are minimized
• AI engagement gathers insights from customer and employee AI feedback and adjusts the message as necessary to drive the culture in a productive manner
• AI product adoption redesigns the workflows, educates employees and customers and build awareness to drive the customer satisfaction and reliability

Simply put, if your business strengths are built into your AI structures, you will protect and build-on these strength through AI.  There is a lot more to developing the right strategy, managing these costs and ensuring the right stakeholders are engaged, but the creative brilliance, leader alignment and value-based selection begins with the right structure.  For more insights into building and managing your AI Center of Excellence visit our A-HUMAN-I site.

2. Where can AI free our teams to focus on strategic thinking and creativity?

The most powerful AI innovations will emerge not from machines replacing humans, but from technology and human collaboration.  Yes, there will be tasks that will be replaced such as analyzing and summarizing documents, but these should give employees time to focus on more meaningful strategic, creative and decision-making activities.  Through human and AI collaboration, we have the potential to:

• Improve the quality and speed of our work – AI like ChatGPT, Claude and Perplexity can produce content much faster and often with better quality which improves our work product and productivity
• Offer new possibilities to supplement our work – Legal AI can quickly find intriguing precedents which introduce new legal argument options along successful outcome predictions
• Replace repetitive and often mundane tasks – AI can monitor organization phishing attempts much faster and thoroughly thus giving cybersecurity professionals more time to focus on new cyber strategy
• Co-create ideas and products faster – Architects and AI can co-design innovative and cost-efficiency buildings that optimize space configuration, energy efficiency and so much more in much shorter time

This AI transformation will create more time, possibilities and new ways of thinking.  The bigger challenge now is supporting employees to rethink how they work and engage customers effectively with new AI.  The World Economic Forum’s Future Jobs Report 2025 estimates humans currently perform 47% of their work tasks, 22% is done by technology and 30% is collaborative.  By 2030, human, technology and hybrid will equally complete work tasks[4] although I would expect AI to complete even more by 2030.  As these digital colleagues are introduced, businesses must reconsider how they prepare, evaluate and reward employees with specific attention on organizational design, culture and workflow.

• Organizational restructuring - Many jobs will be replaced and most, if not all, reconfigured. This includes rethinking how departments and teams work together, changes to your talent strategy, and major learning and development needs.  Organizational structures, job titles and role descriptions will be reconfigured, and new job will appear such as AI Maintenance Specialist.  Additionally, manager roles will shift to support and supervisor AI collaborative results.  Organizations need to rethink these areas along with recruiting, performance management and compensation.
• Culture - Preparation for AI requires a new mindset for your organization. This starts with an AI enterprise engagement strategy.  Your engagement strategy should define:
  • An enterprise AI communications strategy to build awareness about your AI strategy, guidelines, product launches, impacts to employees and customers, and AI successes
  • An enterprise AI learning and development approach for all employees to build AI fluency and prepare for key role accountability changes such as increased decision-making, creativity and output analysis
  • Strong product adoption practices and measurements to drive customer satisfaction and employee behavior change
• Workflow – New products should be designed with employee and customer workflow in mind. Employees interface with multiple technologies every day.  Adding in AI could complicate the workload and can cause “productivity paradox” - a decline in efficiency if a thoughtful product adoption and workflow design is not executed well.

The organizations that thrive in this new era will be those establish the right structures early-on, shift the cultural mindset and make strong AI choices that truly are value-based.

3. What does leadership look like in an AI augmented workplace?

To become a powerful AI leader, critical shifts include mastering AI fluency, leadership adoption role, agile collaborative teams and govern behavior shifts and risk.

AI-Savvy Leaders

To lead AI, one must understand AI.  An AI leadership fluency journey begins with:

• Leader AI basics courses:
  • AI leadership basics – Building an understanding of how AI works, how it is evolving, and how leaders need to shift behaviors to support this new way of working
  • Optimizing AI – Driving business value, data-infused decision making, innovative thinking, ethics, policy development, strategic team integration, and human resource and behavioral supports to produce AI value
• Clarity on the enterprise AI strategy – Leaders need to know where the organization is headed before their employees. Invite key leaders to be a part of the governing process and give them practical and timely awareness of what is happening, how they can support and impacts to their teams.
• Hands-on experience with AI – Hands-on approaches or workshops go a long way to instilling practical knowledge of AI tools
• Advisory coaching to support their learning curve – Having a safe go-to resource to ask simple or complex questions can guide leaders to develop and fail faster

Mastering Adoption

Guiding employees on the AI integration journey is a leader’s primary responsibility.  Employees want to know how their role are shifting and what they need to do to be successful. Many of them are concerned about their learning curve and how AI will change or potentially eliminate their position.  Create an environment where it’s acceptable to make mistakes and fail fast whether you are leading an effort or are impacted by AI.

Leaders may be accountable for key roles on the new product launch.

• AI Sponsor – When you are leading a major change, communicate the who, what, why, when and how for the organization through a strong communication strategy, change networks and training that clearly drives change.
• AI Champion – As a supporter of the effort, understand the impacts to your team and how you bring them along the path. You’ll provide the deeper dive into clarity and transparency for your team on how their role is shifting; how they need to shift and what tools are ready to support this transition.  Be the voice of change and provide the light for your team through this transition.  There will be tough conversations, but your team is looking to you for that guidance early and often.

Customer adoption is clearly crucial to product success.  Their engagement should include focus groups, pilots and options.  Impacted leaders must ensure their customer groups, whether external or internal, are included, considered and engaged.

The list below explores potential adoption ideas that leaders should be monitoring on their teams to ensure the AI launch goes smoothly.  Too many organizations are only focusing on technology development (data, infrastructure and algorithms) and miss the people and process needs to truly launch a successful product.

Reinforce Ethical AI Adoption and Governance

Guide your teams through leading-by-example and addressing challenges as they occur.  Your leadership will set the tone for how your team adapts.  With AI, there are a lot of unknowns and that makes humans uncomfortable.  Mistakes will be made, but how you lead during those times of difficulty will either enforce a new way of working or slow the inevitable future.  Create and share policies and procedures so your team alerts you quickly if they find any potential data bias, privacy issues or any other ethical concerns.

Leaders in an AI-driven world must be learners, communicators, change champions, agile architects, and ethical role models. By embracing these values, leaders can guide their organizations through AI transformation with clarity, integrity, and purpose.

Conclusion

In conclusion, there is a lot to learn on the AI journey.  Whether you are just starting out or need to integrate your human strategy as part of your AI strategy, bring in an experienced AI strategist.  Yes, hiring consultants or top talent can be expensive, but investing in the right expertise will save you time, frustration and money in the long run.  AI is evolving rapidly and those of us in the thick of it are learning and adapting everyday too.  If you want a competitive AI edge, you need experts who live and breathe AI and have unique skill sets of strategy, vision, adoption know-how, data and technology.

www.a-human-i.com

 

[1]PwC, Global Artificial Intelligence Study: Exploiting the AI Revolution

[2] IBM, 6 Hard Truths CEOs Must Face, May 2024

[3] Cisco 2024 AI Readiness Index, Oct 2024

[4] World Economic Forum, Future of Jobs Report 2025, Insight Report, Jan. 2025