Hello, fun topic. Here are my thoughts. I've worked with a lot of journalists on topics like this. 1. Beyond AI, what should be a CIO's top priority in 2026? I believe the top priority should be building strong design thinking and critical thinking skills across the IT organization. The World Economic Forum's Jobs Report highlights the top skills needed by 2030, and many of them aren't traditional technical skills. They focus on creativity, analytical thinking, problem solving, and understanding complex systems. As AI takes on more technical work, these human skills become the real differentiator. 2. What makes this priority urgent? AI will handle more routine tasks, so teams must get better at defining problems, designing better experiences, and making good decisions with imperfect information. Companies that don't build these skills will struggle to innovate. AI only amplifies the thinking you already have. 3. What's the best way to address this priority? Create regular spaces for design workshops, brainstorming, and problem framing. Encourage exploring multiple solutions instead of locking into the first idea. Invest in training that grows reasoning, creativity, and structured thinking. Treat these skills like muscles that need constant practice. Here's a cheat sheet I created on design and critical thinking training options: https://bit.ly/4i7yzRr 4. How will this priority affect the CIO's role? The CIO becomes a champion for how the organization thinks, not only what it builds. Instead of focusing mostly on technology choices, the CIO guides teams toward better questions, clearer problem statements, and more intentional design. The role shifts from operator to creative leader. 5. How will this priority help the enterprise? It leads to better products, better customer experiences, and smarter decisions. When strong thinking pairs with AI-driven execution, teams move faster and build solutions that actually solve the right problems. It also creates resilience because teams with strong critical thinking adapt quickly when the unexpected happens. 6. Anything else to add? The future of IT isn't only technical. The World Economic Forum lists creative thinking, analytical thinking, resilience, curiosity, and systems thinking among the most valuable skills by 2030. CIOs who invest in these capabilities will build teams that thrive as technology continues to accelerate.
1. Beyond AI, what should be a CIO's top priority in 2026? Based on the collective insights from our CEO roundup, where we interviewed 20 tech leaders of global software houses (https://itprofiles.com/resources/how-ai-is-transforming-software-development), a CIO's top priority in 2026 should be "building an AI-ready organizational culture". Counterintuitive, sure, but, one that combines human judgment, data literacy, ethical awareness, and cross-functional collaboration. 2. What makes this priority urgent? Every leader we interviewed emphasized that AI adoption is outpacing organizational readiness. Teams are experimenting faster than companies can align practices, policies, and skills. This creates risks in quality, security, and accountability. As one CEO noted, "AI multiplies mistakes as quickly as it multiplies results." If culture, governance, and skills don't mature in parallel with technology, enterprises risk instability and poor decision-making at scale. 3. What's the best way to address this priority? Invest in holistic enablement. This includes structured training in AI literacy, critical reasoning, and ethical use; building governance frameworks that define human oversight. Several leaders stressed the importance of experimentation zones: safe spaces where teams can learn AI tools, fail fast, and develop confidence without jeopardizing production environments. 4. How will this priority affect the CIO's role? It will shift the CIO from being primarily a technology leader to becoming a culture architect and strategic educator. CIOs will spend more time guiding teams, shaping responsible AI practices, and driving organization-wide alignment. Their influence will move closer to business strategy, risk management, and talent development. In many ways, the CIO becomes the bridge between innovation and accountability. 5. How will this priority help the enterprise? A mature, AI-ready culture enables faster innovation, stronger decision-making, and more resilient operations. It reduces errors, improves collaboration across technical and non-technical teams, and ensures AI is used where it adds real value, not just where it is fashionable. 6. Is there anything else you would like to add? The voices in our roundup make one thing clear: AI is not the destination. It's the catalyst. The organizations that thrive in 2026 will be those that pair intelligent technology with intelligent culture. The CIO's true role is to make that culture possible.
Securing AI systems is quickly becoming one of the most serious responsibilities on a CIO's agenda. As organizations shift from experimentation to full-scale adoption, AI is now informing decisions, guiding operations, and interacting directly with customers. That influence means a compromised AI system can impact every workflow connected to it. Part of the urgency comes from the changing behavior of attackers. Instead of just targeting networks or applications, they now probe models, training data, and prompt flows. If an attacker can influence any of those layers, they gain leverage over how the organization makes decisions. Traditional security controls weren't designed for this. Many organizations are also overlooking a critical dimension: how their data is used by AI tools. When teams build custom GPTs or internal assistants, they need to understand what information the tool can access, how employee inputs are stored, and how providers like OpenAI handle that data. This requires clear oversight of which internal documents and sources these systems can reach and how that data is processed or retained. For companies building SaaS platforms, the responsibility goes even further. AI libraries, third-party services, and embedded models often interact with customer data. CIOs must set and maintain guardrails around those interactions, understand how each component uses or transmits data, and ensure those boundaries are reviewed regularly, especially as AI services evolve. Addressing these risks requires a practical AI security framework. Every model needs clear identity controls, regular adversarial testing, visibility into how data and prompts move through the system, and verification steps for AI-driven actions. These measures help ensure that AI systems behave consistently and predictably when operating at scale. As AI becomes embedded in daily decision-making, the CIO's role expands from managing infrastructure and data to protecting the integrity of the organization's judgment.
Beyond AI, the top priority for 2026 must be "Operational Resilience" and modernising legacy infrastructure to support hybrid agility. This is urgent because technical debt is now the primary bottleneck preventing companies from actually deploying the AI tools they are buying. The best approach is a ruthless audit of legacy systems, retiring anything that cannot support API-driven integration. This shifts the CIO's role from "keeper of the lights" to "architect of business continuity." A resilient enterprise can absorb market shocks and pivot strategies without IT becoming the anchor that holds them back.
The top priority for CIOs in 2026 is actually influenced by AI and the increasing use of Agentic AI in businesses. This priority requires CIOs to ensure their organizations have increased cybersecurity systems and resilience to match the increased threats posed by Agentic AI. This is not a small undertaking and requires breaking down traditional silos between CISOs, CIOs, and CTO domains, and continuous collaboration between development and security teams to enhance the organization's security posture. This means assessing risks, responding to risks proactively and in real time, and developing evolving playbooks that align with OWASP and other state-of-the-art security frameworks. For many enterprises, this may also mean developing new hybrid roles within the organization that provide expertise in AI systems, software development, and cybersecurity. Attention to these risks and having an AI security strategy in place are competitive signals that investors, other business partners, and increasingly consumers will look for, helping the competitive positioning of a company. I have recently written more about this topic on my Substack, here: https://substack.com/home/post/p-178376234
1. Beyond AI, what should be a CIO's top priority in 2026? Data resilience infrastructure. As organizations rush to implement AI and cloud solutions, they're creating massive new data dependencies without corresponding recovery capabilities. CIOs must prioritize comprehensive data resilience that goes beyond basic backups. 2. What makes this priority urgent? The average cost of data loss now exceeds $4 million per incident, and recovery time directly impacts competitive positioning. With AI systems generating and consuming unprecedented data volumes, a single failure in your data pipeline can cascade across operations, customer experience, and revenue streams within hours, not days. 3. What's the best way to address this priority? Conduct a data dependency audit mapping critical business processes to their data sources, implement multi-layered recovery strategies with regular restoration testing, and establish clear RTOs (Recovery Time Objectives) for each system tier. The key is treating data resilience as business continuity, not just IT backup. 4. How will this priority affect the CIO's role? It elevates the CIO from technology manager to business resilience strategist. You'll need to quantify data risks in business terms, collaborate directly with business units on continuity planning, and demonstrate how data resilience drives competitive advantage and customer trust. 5. How will this priority help the enterprise? Beyond preventing catastrophic losses, robust data resilience enables faster innovation, supports aggressive digital transformation, reduces insurance costs, strengthens customer confidence, and provides a measurable competitive differentiator when pursuing enterprise clients who demand proven business continuity. 6. Is there anything else you would like to add? After 24 years in data recovery serving Fortune Global 500 companies, I've seen that organizations don't fail from lack of technology—they fail from untested assumptions about their ability to recover. Test your recovery processes quarterly, not after disaster strikes.
1. Beyond AI, what should be a CIO's top priority in 2026? Building a disciplined system for organizational change. We've all seen the pattern: companies rush to adopt new technology, but without a framework for evaluating, implementing, and scaling it properly, most initiatives either fail or never deliver meaningful value. What CIOs really need is a repeatable process: start with small, contained experiments, measure what actually matters, document what you learn, and only then scale what proves itself. 2. What makes this priority urgent? AI and automation projects fail at alarming rates, and the culprits are predictable. Teams get paralyzed trying to navigate compliance and governance questions—or, worse, skip those conversations entirely, creating risk. Without clear guardrails, organizations either overspend on "shiny object syndrome" or stall out completely when legal and security teams raise concerns about data handling, tool usage, and policy gaps. 3. What's the best way to address this priority? Start with what I call the mini-experiments approach. Run scoped pilots with clear boundaries and human oversight. Establish your baseline metrics from day one—cycle time, quality, incidents, rework—whatever matters for that specific use case. Learn from what works and what doesn't, then promote the winners into standard operating procedures before you automate further. 4. How will this priority affect the CIO's role? CIO is no longer just the person who evaluates and buys tools. They become the orchestrator of disciplined organizational change. That means owning policy clarity, driving process mapping, establishing measurement frameworks, and building the pipeline that turns successful pilots into durable procedures. It requires a much closer partnership with security, legal, and product teams. Honestly, it's a harder job, but it's also a more strategic and impactful one. 5. How will this priority help the enterprise? In practical terms: faster, safer technology adoption with demonstrable ROI. Less work sitting in limbo because teams are afraid of compliance issues. Significantly reduced waste—you're only scaling what's proven to work. Lower risk across the board. 6. Anything else to add? A few things I've learned: Keep your guidance pragmatic and concise. Short, actionable guides beat comprehensive policy documents every time. Always measure before and after—if you can't prove value, you can't defend the investment or justify scaling.
1. Data infrastructure modernization must be every CIO's paramount focus. While AI dominates boardroom conversations, the unglamorous reality is that most organizations lack the data architecture needed to extract real value from these technologies. Without clean, accessible, well-governed data pipelines, AI investments become expensive experiments rather than transformative tools. 2. The AI revolution is accelerating faster than enterprise readiness. Companies rushing to deploy generative AI are discovering their data is siloed, inconsistent, or trapped in legacy systems. The window to build robust data foundations is closing - organizations that delay will find themselves perpetually behind, unable to leverage AI breakthroughs as they emerge. 3. Start with a comprehensive data estate audit. Identify critical data sources, quality issues, and integration bottlenecks. Implement a cloud-native data platform that enables real-time access across functions. Establish clear data governance frameworks that balance accessibility with security. Invest in master data management, data catalog, knowledge graphs, and data quality controls. Most importantly, break down organizational silos - data infrastructure is everyone's responsibility, requiring collaboration between IT, business units, and data science teams. 4. CIOs must evolve from technology managers to strategic data architects. This means becoming fluent in data economics - understanding which data assets drive business value and how to monetize them. CIOs will spend more time with business leaders, translating data capabilities into competitive advantages. 5. Solid data infrastructure unlocks exponential value. AI models perform better with quality data. Analytics become faster and more reliable. Compliance risks decrease. Innovation accelerates as teams can rapidly prototype data-driven solutions. 6. Remember: AI is only as intelligent as the data it consumes. Build the foundation first, and transformation follows.
As organizations grow more comfortable with AI, 2026 will be defined by a shift from experimentation to scaling. The biggest movement that is "in" is the continued acceleration and deeper operational embedding of AI and Machine Learning. This isn't hype. It's tied directly to top enterprise priorities: improving efficiency, strengthening decision-making, and unlocking deeper insights. For accounts payable (AP), AI is already proving valuable in automated invoice processing, intelligent exception handling, and fraud detection, and the returns are strong. AvidXchange recently surveyed more than 500 finance and AP leaders and found that AI adoption is driving measurable impact: increased efficiencies (48%), faster insights (40%), and improved data quality through fewer errors (38%). Complementing AI, automation and workflow platforms are becoming core infrastructure rather than "nice-to-have" investments as they are crucial for achieving sustainable productivity and meeting SLAs. Security and governance will also take center stage. For finance teams, fraud concerns remain the biggest obstacle to modernization, and the data backs it up. Through our survey, we found that high-priority actions include enhancing cybersecurity monitoring (52% of teams) and strengthening payment security controls (47%). This focus on security and regulatory compliance necessitates strong data governance and control to mitigate risks like check fraud and phishing. When it comes to skill sets, technology fluency and data analysis capabilities - not just traditional accounting experience - are becoming essential. Financial institutions want professionals who can operate, interpret, and optimize within increasingly technology-driven environments.
In 2026, beyond AI, a CIO's top priority should be safeguarding identity infrastructure, which research firms like Gartner have already flagged as a rising enterprise risk and budget sink. This priority is urgent because attacks are no longer about breaking firewalls — they target credentials, privileged access, and the sprawl of unmanaged identities that slow migrations and expose the business to catastrophic downtime. The best way to address it is by consolidating IAM into cloud-first platforms, enforcing least privilege, and deploying AI-powered anomaly detection so identity becomes a moat, not a liability. That shift will rewrite the CIO role — from systems curator to identity architect — because every roadmap, vendor choice, and scale decision now has to originate from "who has access and why." When identity is treated as infrastructure, not overhead, the enterprise moves faster, sleeps safer, and builds a durable foundation for every digital bet in the stack, all of which ultimately benefits the enterprise by reducing breach blast radius and accelerating secure innovation.
CIO's top priority in 2026: The single top priority must be threat-priority selection. That means deciding which detected threats to treat first based on business impact, exploitability, and exposure. CIOs cannot simply let their teams fix the topmost alert in a queue. Cybersecurity threat detection has matured a lot in the past few years, especially with AI coming into the picture. But the real failure mode today is insufficient prioritization. Too many security alerts without a clear priority become noise. What makes this priority urgent? With more advanced tools, cyber threat alert volumes and false positives have also grown. If teams keep treating each alert as equal, it guarantees burnout and missed high-impact incidents. Business complexity (like cloud sprawl, third-party access, hybrid work) further increases the surface area and makes just 'intuition' unreliable for prioritization. Even a small lapse can lead to major regulatory and compliance violations. That's lost money, ruined reputation, and lost trust. What's the best way to address this priority? I suggest that CIOs start by mapping critical assets and business impact. Then implement a risk-scoring model that combines exploitability, asset criticality, business impact, detection confidence, and exposure window. Make sure to integrate context from CMDB, identity stores, cloud posture, and business application owners so scores are grounded in reality, not just telemetry. Then build decision playbooks that mark priority tier, define who acts, what actions are permitted, and what escalation looks like. How will this priority affect the CIO's role? Today, a CIOs success is not measured by how many alerts are caught, but more by how few high-impact incidents reach the business. Risk prioritization models will help CIOs deliver on grounds that really matter. How will this priority help the enterprise? Businesses have finite security capacity. Risk prioritization helps focus resources on measurable gains. Is there anything else you would like to add? Cyber threat prioritization is as much a cultural problem as a technical one. Letting teams know this is a P1 issue isn't enough. CIOs need to incentivize teams to fix the highest-risk issues first, even when those issues are not the easiest. This 'incentive' will look different for every organization, but it is important, nonetheless. Priority lists won't matter unless someone actually does something about it.
For 2026, I'm focused on rebuilding our data infrastructure. Fragmented data and old systems kill innovation faster than anything else - you need clean, connected data that people can actually access. That's what makes AI and automation worth the investment. The pressure is real too. Cyber threats don't slow down, and legacy platforms crack under load. I've watched companies rush into AI without fixing their foundation first. The tools were fine. The data and infrastructure couldn't keep up. Projects just collapse. So I start by mapping where things actually break. Then I build a single source of truth and enforce basic rules so data stays consistent. I prioritize fixes that remove friction and unlock analytics and automation. Every upgrade has to tie back to business outcomes or it becomes dead cost. I'm also hiring and training people in cloud, data engineering, and security. That's where the real leverage is. Being a CIO used to mean keeping the lights on but now it's about inspiring change.
1. Beyond AI, a CIO's top priority in 2026 should be building a resilient and adaptive data infrastructure. As every function from marketing to finance depends on real-time, trustworthy data, the ability to scale, govern, and connect data systems is what makes transformation stick. 2. The urgency comes from two forces converging—rapid decentralization of tech decision-making across business units and increased regulatory pressure around data privacy and security. If your architecture can't flex and respond to both, your entire enterprise becomes exposed. 3. The best way to address this is to stop thinking about data as a backend utility and start treating it like a product. Assign ownership, ensure discoverability, implement quality checks, and design for self-service. That turns IT from gatekeeper into enabler. 4. This shift expands the CIO's role from system integrator to business enabler. You become the steward of how information flows through the organization, which means closer alignment with product, legal, customer experience, and strategy teams. 5. When data is clean, accessible, and actionable, enterprise decisions get faster, forecasting improves, and innovation cycles shorten. It's the infrastructure that unlocks agility. 6. CIOs who master AI will win headlines. CIOs who master data will build empires. You can't have one without the other—and only one creates lasting value.
Beyond AI, the top priority for CIOs in 2026 will be rebuilding digital trust inside the enterprise. Not cybersecurity alone — trust. Employees, customers, and partners are all adapting to tools, workflows, and decisions that move faster than their comfort level. When trust erodes, adoption slows, shadow systems appear, and even the best tech investments fail to land. It's urgent because companies are now running on layers of automation, data sharing, and real-time decisioning that depend on people believing the system is safe, accurate, and fair. The gap between what leaders roll out and what teams actually embrace is widening. CIOs can't afford that gap anymore. Without trust, AI, cloud, and automation don't scale — they stall. The best way to address this is to build transparency into every layer of technology. Clear data policies. Visible decision logic. Honest communication about where automation supports people and where it replaces steps. CIOs who explain the "why" and not just the "what" see adoption skyrocket. It also means tightening up governance without slowing the business down — automated controls, real-time guardrails, and human-review loops where judgment matters. This shift will reshape the CIO role. The job will feel less like a systems architect and more like a translator, strategist, and relationship builder. The CIO becomes the person who turns fast-moving technology into something people actually trust enough to use. That requires emotional intelligence just as much as technical depth. For the enterprise, trust has a compounding effect. It improves adoption, reduces internal friction, and makes transformation stick. Teams move faster because they're not second-guessing the tools. Leaders make better decisions because the data behind them is believed, not debated. Security posture improves because people follow the rules instead of working around them. If CIOs focus on trust as seriously as they focus on AI, 2026 won't just be a year of new technology — it will be a year where that technology finally works the way it was intended.
I'm going to answer this from my 20+ years running large-scale conferences and corporate events, where system failures mean 2,500+ attendees staring at blank screens while your keynote speaker waits backstage. **Cross-functional communication infrastructure** is what keeps me up at night, and it should be every CIO's priority. When we scaled The Event Planner Expo to become the leading industry conference, the breaking point wasn't technology--it was that our registration team, venue tech staff, and marketing couldn't talk to each other in real-time. We lost a $40,000 sponsorship deal because three departments had conflicting information about booth specs. I implemented a unified communication protocol where every stakeholder operates from one shared run-of-show document, and our error rate dropped 73%. The urgency is brutal: when Google or JP Morgan sends their team to our events, they expect seamless experiences. One miscommunication between IT and operations means their VP is locked out of a breakout session they flew across the country to attend. CIOs need to stop thinking about communication tools as separate from operational systems--they ARE the operational system. This shifts the CIO from technology provider to operational translator. At our events, I brief every team before doors open because everyone needs to understand how their piece affects the whole machine. Your enterprise works the same way--sales needs to understand what IT can actually deliver, and IT needs to speak in terms of customer impact, not server uptime percentages.
1. The CIO's second greatest priority behind AI in 2026 is to create the resilient, real-time data structures. What I see in advancing, fast-moving tech environments is that AI is only as good as the data it reads (is fed). The true competitive advantage today is to have clean, connected, usable data immediately available to every area of an organization. It is clean data available to make real time decisions in every relevant part of the organization that connects to performance gains and operations improving dramatically not dated, back office siloed insights or back office delayed reporting. 2. The sense of urgency comes from the pace of decision-making. The operating and tactical environments of markets, investor expectations and risks are changing far too quickly for a weekly or even monthly data reporting cycle. I am witnessing companies being blindsided simply because they couldn't turn accurate information fast enough from their systems. 3. The best way to solve data cycle challenges is with a single source of truth data layer and governance around it. This means linking the operational systems, establishing data ownership and governing quality. Once the foundation has been laid, any AI, analysis or automated work can then become exponentially easier, better and faster in its delivery. The above objectives will effectively help decision-making organizations. 4. This priority elevates the CIO role to that of technology operator (more traditional managing of systems) to steward of truth (more influence across functional lines). The CIO is now being asked to hold the assurance that executive decisions they made are based on reliable data based, real-time intelligence. Again, it is evolving away from service provider to influencer.
A CIO's top priority in 2026—beyond AI—should be strengthening digital resilience across the entire organization. I've seen firsthand how quickly operations can unravel when systems aren't prepared for rapid change, whether it's a sudden traffic surge, an unexpected outage, or a shift in customer behavior. The urgency comes from the fact that most companies have layered on new tools and cloud platforms faster than they've secured or integrated them. The result is a fragile ecosystem where one weak link can slow down the entire business. Digital resilience isn't just about cybersecurity—it's about ensuring continuity, adaptability, and reliability at every layer of the tech stack. The most effective way to address this is by centralizing visibility and tightening governance around data, infrastructure, and workflows. When I worked with a client who launched a large-scale SEO campaign, their website kept crashing under the increased user load. The fix wasn't more software—it was redesigning their systems to scale, improving cross-team communication, and building processes that didn't rely on a single point of failure. CIOs need to treat resilience like an ongoing discipline: regular stress testing, scenario planning, and patching organizational bottlenecks before they become operational crises. This expands the CIO's role from "technology overseer" to "business stabilizer," someone who anticipates problems before the business feels them. A strong resilience strategy ultimately helps the entire enterprise move faster with fewer risks. Marketing teams can launch campaigns without fearing downtime, product teams can ship faster, and leadership can make decisions backed by reliable data. CIOs who invest in resilience now will create organizations that can innovate with confidence, even as new technologies like AI continue to reshape the landscape. The companies that win over the next decade won't be the ones with the flashiest tools—they'll be the ones that stay standing when everything around them shifts.
After building 500+ websites and managing digital infrastructure for small businesses, I've seen one thing sink companies faster than outdated tech: **security debt and vendor consolidation**. Most CIOs are juggling 15-30 different SaaS tools that don't talk to each other, creating authentication nightmares and data silos that hackers exploit daily. The urgency hit me hard when one of our e-commerce clients got breached through a forgotten third-party plugin we'd integrated two years prior. Cost them $47,000 in downtime and customer trust. That's when I implemented what I call the "3-platform rule"--consolidating client tech stacks to maximum three core platforms that handle multiple functions securely. Best way to address it? Audit every vendor relationship quarterly and ask "does this tool justify its own security risk?" We cut our clients' average tool count from 19 to 8, reduced their combined software costs 66%, and eliminated 80% of potential breach points. One agency client went from managing five different payment processors to one unified system--their PCI compliance audit went from nightmare to done-in-a-day. This turns CIOs from tool collectors into risk eliminators. When we streamlined one client's WordPress stack from 47 plugins to 12 core solutions, their site speed doubled and their bounce rate dropped 40%. Less complexity means faster responses when threats emerge, and your team actually understands what they're protecting.
I'm Tim Johnson, co-founder of BIZROK. After years in leadership across military, corporate, and startup environments before launching my consulting firm in 2021, I've seen how operational bottlenecks kill growth faster than technology gaps. Here's what I'd prioritize: **Leadership development and succession planning** should be your top priority. I watched my father's small business thrive financially but fail operationally because he couldn't step away--he missed every out-of-town tournament I played in. CIOs face the same trap: technical expertise without scalable leadership creates a single point of failure that caps organizational growth. The urgency is real because knowledge transfer doesn't happen during a crisis. When we launched BIZROK, we immediately built systems where every team member--Jasmine, Rebecca, Cassie--can operate independently with decision-making authority. Our dental practices grow 40-60% not because we're smarter, but because we eliminate the "only I can do this" mentality that most technical leaders fall into. Address it by documenting decision frameworks, not just processes. I teach practice owners to create "leadership operating systems"--clear protocols for judgment calls that let teams act without constant approval. One client went from texting their office manager 47 times during a vacation to zero interruptions in six months because we built confidence through systematic delegation. This shifts CIOs from technical gatekeepers to organizational multipliers. Your enterprise scales when solutions don't require your personal involvement, and your career advances when executives see you building leaders instead of managing tickets. The freedom to focus on strategic work instead of operational fires is the actual ROI--I learned that from missing my dad at those tournaments.
1. Beyond AI, what should be a CIO's top priority in 2026? Developing a reliable and future-proof digital infrastructure. Quick changes in the platforms, security issues, and customer requirements should all be taken into account when talking about the importance of stability and scalability-to-note, these are as important as innovation. 2. What makes this priority urgent? It is urgent as a large number of organizations are still using outdated technology which is very expensive for them. Old systems are a cause of delayed decisions, security risks and limit the ability to experiment including AI itself. 3.What's the best way to address this priority? The most effective way is to implement a phased modernization plan consisting of conducting an audit of legacy systems, organization-wide data unification, cloud environments upgrade and clean internal process investment. It is just like housekeeping that facilitates the transformation rather than being an obstacle.