The deeper I go into understanding and operationalizing AI in organizations, the more I retain the right to be wrong about everything that I think. AI is a society-altering technology on the level of electricity, gun powder, and the wheel; do we finally realize a Star Trek-esque, post-scarcity global society, are we to descend into a bleak Altered Carbon oligarchy, or maybe something out of James Cameron’s quill circa 1982? The topics below are based on my personal experiences and observations over my career. Every item could be the subject of its own dissertation and there will always be edge cases to quibble over.
AI Implementation Is Organizational Change Management (OCM)
When you deploy AI into your environment you change the very nature of what work is across your entire enterprise. How you operate, budget, hire, train, maintain, etc., all will shift.
Metrics: If you’re searching for metrics to measure how your AI implementation is going, just look to OCM. Adoption rate, training completion, customer satisfaction, et al., are all OCM metrics that are readily adaptable for AI implementation programs. If you’re changing the organization, then you are best served by metrics that were designed to manage change.
Culture: Organizational culture is the sum of the daily behaviors of everyone in the organization. Therefore, changing the culture of an organization is nothing more than a collective change of individual behaviors. So, if AI implementation is going to change the work you do, that is a significant change to your daily behaviors and habits, isn’t it? Congratulations, your organization’s culture has just shifted into learning mode. You can either embrace it and flourish, or fight against it and deal with that pain on top of other adjustments you’re having to make.
On Strategy: Always start with why. AI is a brand-new technology that requires a paradigm shift across all types of organizations, so be flexible with yourself and be gracious with others. Learning is a human endeavor, and we all learn at different paces. However, that learning curve needs to be bracketed by strong ethical governance principles and their application within your organization (this is where AI-fluent legal counsel finds a niche) and throughout your market sector. AI adoption is based on trust, it doesn’t matter if that adoption is internal to the workforce or external facing the customer.
AI and Money
AI incorporation significantly affects the financial operations of an organization. It impacts how you budget, your tax write-offs, and your daily financial operations.
Investment Costs: Deploying AI requires significant upfront investment in technology, training, and infrastructure. Ensure you have a clear budget and financial plan to avoid any funding issues. The better you can plan, the tighter your operations (same as with anything else).
CAPEX to OPEX: Typically, IT system deployments are considered capital expenditure. However, AI is an operational cost due to its computation needs, storage requirements, and enterprise utilization. This is markedly different line of thinking when it comes to budgeting and taxation. Deductions, depreciation vs. expense, cash flow impacts, reclassifications, etc. Books are written about this topic, and chances are your org will need to adjust.
Hybridized Finance Roles: If you’re someone who works in finance, remember that your job isn’t going to be lost to AI, your job will be lost to someone who knows AI. The best hedge against an imminent career change is to learn zero-based budgeting, overlay that with a solid understanding of cloud financial operations (FinOps), and set both of those on a foundation of Software-as-a-Service (SaaS) fundamentals. That should cover most of your core knowledge base for AI FinOps. The remaining knowledge gaps usually end up getting filled by institutional knowledge and your network.
Acquisitions and Changing Expectations
AI implementation also impacts real and accountable property management and your business development operations. As everyone has seen since the pandemic, remote work isn’t going away and will expand as more sectors embrace AI and the old organizational dynamics shift.
Accountable Property: Once your organization realizes what is possible via AI, one line of effort will extend here. Get ready for a smart grid, sensors collecting data along your entire value chain, and a whole new endpoint lineup and refresh cycle. Essentially, the corporate attack surface is about to vastly expand, and these operations will have to be incorporated tightly with your cyber team. Get your inventory management processes tight and start reading up on physical security and cybersecurity with an emphasis on endpoint protection if you’re in these types of roles.
Real Property: Full-time, in-office work is a relic of the Information Age economic model, and no amount of wishful thinking or denial of market trends will ever make it great again. As AI augments the global workforce, commercial real estate could flex into needed third spaces to further incorporate your organization into the local community. As intelligence is democratized, creative talent and culture becomes your businesses differentiator.
Figure out what your community needs (adult day care, post office, sculpture garden, etc.) and build that for your community. AI will allow us to move further apart from each other into our own information silos, and the things that bring us together will elevate in value. If you work in real property, start learning about robotics; you’ll need to understand the basics of that field to better manage/maintain your future security guards, cleaners, and maintenance T-600’s.
Contracts: If AI increases your OPEX and decreases your CAPEX, then the cash flow established by your contractual agreements must shift to allow for that downstream adjustment. You’re going to have to incorporate a billing mechanism if you’re leveraging an LLM, computer vision, anomaly detection, or other AI solutions for your customers’ business needs. The more you use AI, the more your operating costs increase (compute and storage), the more you must charge to cover those costs. Major AI providers have cost analysis modules available to help with forecasting and budgeting, but it is up to you in finance/acquisition roles to be knowledgeable enough in these tools to leverage them.
IT Merges With HR
Augmenting your organization with generative AI (GenAI) means that your front-line workers will now have to leverage management and supervisory skills over those GenAI instances. This leads to demand signals for IT to take on some HR functions:
IT will manage AI agents: IT isn’t a cost sink for your business, IT is your business and its ability to function. As agentic AI proliferates through 2025 and into 2026, the IT department will need to develop HR capabilities to “manage” the agents operating throughout your business — think performance evaluations for GenAI. Additionally, IT will be the final arbiter of how well the human staff performs at interacting with and utilizing their respective AI/agents (user level compute and storage costs, prompt optimization, response validity, etc.), linking IT knowledge to the HR performance evaluation process.
Training programs are not optional: AI is a tool. You need to equip yourself and your team with this tool to better compete in your market sector. Upskilling and AI implementation go hand in hand as shown previously in the OCM section, and IT and HR are the nexus of all AI implementation OCM activities. The more time and effort you put forth in training initiatives, culture building, and OCM support, the smoother your AI implementation will be, because these activities are what builds the foundation of your changed organization. If you’re not prepared to operate differently, then once you can operate differently, you won’t be able to.
What to train on? Go with data literacy, data governance, AI tool literacy, and supervisory skills training. The data literacy and governance to expand your corporate knowledge base to accommodate new problem sets and solution identification. The AI tool literacy so people know how to use whatever AI you’re deploying. Finally, supervisory skills training to teach your employees the skills they’ll need to manage the inputs and supervise outputs of AI instances and agents. Humans must stay in the loop to ensure smooth operations (at this stage).
HR gets personal: Individuals need to feel emotionally connected to and psychologically safe with others to form an effective team. As you incorporate AI, human-to-human collaboration will decrease along traditional communication lines. HR’s duties should organically expand to include the continuous team and culture building necessary to fill the communication/culture gaps created by moving humans up the organizational hierarchy by applying AI at the task and process levels where the majority of current human work is performed.
What Can I Do Regardless of Where I Work?
Regardless of what you do, AI will incorporate itself into your life as you simply move through society — you might as well try to avoid electricity. Below are some things to keep in mind for yourself as we shift paradigms:
Get Comfortable Being Uncomfortable: If every organization is adopting AI, if AI adoption changes the way organizations function, and if our society is a series of interconnected organizations, then our society will change as AI implementation proliferates. The lessons of OCM hint that our society will need to become a learning society if we are to succeed in leveraging AI for our collective good. Get on board, get comfortable being uncomfortable, or get left behind and likely be a drag on human progress.
Use AI: Start using AI to get better at understanding how it impacts you. Go ahead and pay $10 monthly (in the U.S.) for Copilot if you have your own MS Office subscription at home and start experimenting. If not that, then Perplexity, Claude, OpenAI, et al, have subscription tiers where you can unlock capabilities and figure out for yourself how AI can augment your personal knowledge, skills, and abilities. You are the subject matter expert on yourself, and like all things in life, you’re going to get out of AI tools what you put into learning them. Using that train of thought, if all these businesses are using AI to make themselves more productive, why aren’t you using AI to make yourself more productive?
What if? You’re in whatever job you’re in and you’ve had whatever career you’ve had up until this point, but what if you could afford to take some classes for that certification? What if you had the money to get your kid a math tutor? What if you lived in a world where intelligence was democratized and barriers to learning were felled using AI? In the Age of Information, ignorance was a choice; in the Age of AI, ignorance is largely irrelevant.
For example, I recently earned my ISO 42001:2023 certification. I learned all the relevant material prompting Perplexity to generate course curriculum, ISO 42001:2023 practice exams, study guides for the exams, grade my exam answers, and then construct follow-up quizzes to buttress any weak areas. The only money I paid was to take the exam and to get a copyrighted edition of the actual ISO 42001 guidance. While the actual material is copyrighted, there are enough blogs, videos, and articles freely available to synthesize a personalized subject matter expert to be a tutor on any subject you wish to learn. It’s that easy, you just need to allocate the effort.
The Times They Are a Changing
Lastly, AI implementation will affect our society overall. Here are just a few things I’ve either been asked about repeatedly or that arise naturally during conversations regarding the social transition into the Age of AI:
40-hour work week has been over: Our society is structured around a 1913 automobile assembly line; 8 hours of work a day, 5 days a week of work is a global standard that is a result of the human transition through the Industrial Age. One of the reasons that current modern life is so hectic and stressful is that we never updated our social models as we transitioned into the Information Age, creating friction points — the need for dual incomes, lack of social support structures such as child and elder care, etc. Overall, the productivity gains didn’t go to the individual, they went to organizations (corporations, governments, etc.) who were enriched and used that new capacity to invest in even more productivity gains. Our global society (by and large) never fully went through that maturation and adoption process. Mostly due to how technology tends to advance exponentially while humans take a much more linear pace with frequent backslides into more brutish modes of thought.
In the Age of AI, what is work? If I’m 20% more productive with AI-enabled operations, then shouldn’t I get 20% of my time back? We’re now talking about 8 hours a day, 4 days a week. But, why not 6 hours a day, 5 days a week? If you’re in the United States, health insurance, unemployment insurance, employer benefits, social benefits are all tied in some fashion to the concept of a 40-hour week that is no longer necessary. This shift alone is enough to destabilize a country; now imagine the collective incoming psychological trauma of hundreds of millions of people (possibly about 1.6 billion using a liberal application of the Pareto Principle) all over the world who are about to realize that the career/endeavor they devoted their lives and personality to (at the expense of relationships, health, etc.), now takes about half the time and the entire Westernized concept of a successful existence changes en masse.
We can’t afford to make the same mistakes transitioning into the Age of AI as we did transitioning into the Age of Information. If the productivity gains enabled by AI are not used to enable the prosperity of as many people as possible, then the aggregated stress of future levels of economic inequality will fracture already stressed governance and social support structures. In sum, if the wealth goes straight to the top like it did with our last transition, then as Alfred Henry Louis said in 1906, “There are only nine meals between mankind and anarchy.”
I keep getting asked about education: I touched on this earlier, but here want to concentrate on the formal education of children and adults. One might presume that if everyone has their own personal Socrates — one that can tailor itself to each learning style, neural divergency, and circadian rhythm for optimal learning — we would no longer need schools. However, this neglects another purpose of group learning — teaching our students how to interact with each other. Schooling teaches students how to be part of a society, moving properly through different environments and situations. Therefore, human teachers will no longer be covered in chalk dust but will be instructing us on how to remain a society through the proliferation of social mores, customs and laws, and by providing a monitored and supervised space for mental and emotional growth with, by, and for others. Qualifying and training teachers with these soft skills and intellectual abilities will be vital to maintaining and promoting a well-functioning society.
So Long and Thanks for All the Fish
Deploying and operationalizing AI systems requires careful consideration and planning across your organization as well as the inherent flexibility and learning mindset needed for change. The more I interact will people of all backgrounds, the more I see a growing demand for casual conversation about the nuts and bolts of what AI means for the individual, society, as well as the desire to scry the future. Keep in mind that these are meant to be answers to common questions and issues that I have encountered, but they are just the tip of the iceberg when it comes to changing the way our organizations and society will need to function in the future to prosper.
Matthew Kilbane is a seasoned leader with expertise in AI Governance, technology business management, and IT program leadership. With a decorated 20-year career in the U.S. Army, extensive service with the Department of Homeland Security, and experience in Fortune Global 250 companies, he excels at building high-performing teams and driving innovation. Holding an M.B.A., advanced certifications, and a background in cutting-edge AI technologies, Matthew brings a passion for problem-solving and advancing technology for positive public and private sector impact.
NOTE: This article is adapted from a seminar given in April 2025 at the Society for Intercultural Education, Training, and Research (SIETAR) Virtual AI Symposium 2025. A fuller version was published in June 2025 in the SIETAR Virtual AI Symposium Conference Proceedings.
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