IDC

In 2011, when Marc Andreessen famously said, “Software is eating the world,” the enterprise software market was valued at $300 billion, making up a respectable 19% of the broader IT market. Today at IDC, we project the market will skyrocket to $1.6 trillion in 2026, capturing 39% of the IT landscape. This explosive growth means that the role of the CIO is evolving, too. Traditionally, the CIO has been responsible for maintaining operational efficiency and minimizing risks. But now, he or she is also expected to drive digital transformation and generate new revenue streams. In fact, our own research shows that 67% of CEOs expect their CIOs to lead digital transformation efforts in the next two years. And that starts with software procurement. Now, just saying the dreaded “p” word might trigger a stress response in any CIO who’s confronted this giant “elephant in the room.” Without the right tools and strategy in place, procurement can feel like an endless cycle of pain points — and every choice can feel like a high-stakes race. One wrong move, and you’re lagging — trampled with overpriced contracts and incompatible tech, or, worse, “supplier ghosting” when you’re desperate for support. The good news? A new wave of AI-powered procurement platforms is stepping up to help CIOs tame the beast. They promise to make procurement faster, smarter, and more strategic, saving your organization time and resources (and, saving your sanity too). Before we dive into why this shift matters — and how AI can transform the procurement process — let’s revisit the pain points that have been wreaking havoc for decades, starting with the all-important RFP. The RFP Challenge: Why It Matters Mastering the Request for Proposal (RFP) process is critical for CIOs. After all, procurement isn’t just about purchasing technology; it’s about aligning tech investments with your organization’s broader business goals, the cornerstone of digital transformation. Traditionally, the RFP process consists of several critical steps: Defining Requirements: Identifying business needs ensures alignment between your organization’s goals and the solutions you’re seeking. Market Research: Thorough research and analysis help identify suitable vendors and solutions. Drafting the RFP: The RFP must clearly communicate the requirements to vendors, soliciting bids. Evaluation: Proposals are assessed to determine the best fit against predefined criteria. Selection and Negotiation: The best solution is selected, and terms are negotiated to establish a successful partnership. The RFP process may seem straightforward — define the problem, invite vendors to bid, evaluate the options, and make the best choice. But if you’ve ever waded through piles of vendor responses, you know it can feel more like a maze of confusion, and losing your way comes with costly consequences. That’s why RFPs remain one of the most valuable yet frustrating aspects of procurement. Their potential to guide informed, strategic software selection is often undermined by: Lengthy Timelines: Traditional RFP processes can extend project implementation timelines by up to three times longer than anticipated. (IDC) Cost Overruns: Our own research found that 44% of CIOs cited the cost of sourcing exercises as their number one pain point in 2024, with external consultants and research adding to the expense. Resource Strain: IT teams, often lacking the business acumen for vendor selection, are burdened with time-intensive manual tasks like contract analysis and supplier evaluation. (CIO) When poorly executed, RFPs can create a domino effect of delays, misaligned vendor relationships, and wasted budgets. Of course, RFPs are just one piece of a larger puzzle. From resource-heavy sourcing exercises to integration challenges, the pain points in procurement can derail even the most promising tech initiatives. Overcoming Procurement Challenges with AI AI-powered procurement platforms can transform the process, helping CIOs overcome common hurdles and make decisions with confidence across the whole procurement lifecycle: 1. Streamlining RFPsWriting, distributing, and evaluating RFPs is like reinventing the wheel every time you need a new tech solution. It’s tedious, time-consuming, and rarely yields the insights you need to make confident decisions. Example: Looking for a new cybersecurity solution? An AI-powered platform drafts a tailored RFP, distributes it to vetted suppliers, and evaluates the responses based on predefined criteria. Fact: AI automates time-intensive tasks like vendor comparison, contract analysis, and data validation, slashing timelines and improving accuracy. (Financial Times) 2. More Confident Decision-MakingAI-powered tools can not only streamline research and reduce redundant trials, but they offer decision-making confidence based on insights from thousands of data points. Example: You’re launching a new office, and your team is stretched thin. AI handles the logistics of sourcing IT hardware, comparing costs, and ensuring timely delivery — freeing your team to focus on relationships and strategy.Fact: AI-driven insights empower CIOs to quickly evaluate vendors with data-backed precision, ensuring alignment with business goals. (McKinsey) 3. Proactive Risk ManagementAI doesn’t just find suppliers — it also screens them. From tracking delivery times to analyzing performance reviews, AI can help ensure you’re partnering with reliable vendors who won’t disappear when you need them most. Example: AI flags a supplier’s declining performance metrics before you renew their contract, saving you from a costly investment. Fact: AI tools quickly assess supplier risks, mitigate compliance issues, and increase transparency in the procurement process. (SAP) 4. Cost Optimization:AI procurement platforms excel at identifying cost-saving opportunities. They’ll flag overpriced contracts, suggest negotiation tactics, and even predict future price trends so you can strike while the iron’s hot. Example: AI notices your organization’s historical spend on IT procurement services and recommends consolidating vendors to unlock bulk discounts. Fact: AI-powered spend analysis highlights savings opportunities and eliminates unnecessary expenses. (McKinsey) 5. Speedy Analysis of Vendor OptionsAI thrives on data. It can analyze your needs, compare thousands of vendors in seconds, and deliver curated recommendations tailored to your specific goals. In short, AI narrows the field, so you’re not wasting time on irrelevant options. Example: You need a new cloud provider. An AI-powered platform evaluates costs, performance metrics, and integration capabilities across dozens of vendors, instantly highlighting the best fits. Fact: 79% of companies report challenges in purchasing B2B software

AI innovation is evolving fast, and DeepSeek has entered the race with an approach that’s catching the industry’s attention. By rethinking how AI models are trained and optimized, DeepSeek isn’t just another competitor—it’s actively challenging some of the most fundamental cost and efficiency assumptions in AI development. As enterprises and AI vendors navigate an increasingly complex technology landscape, the big question is: Will DeepSeek’s novel approach shift the AI market in a meaningful way? And if so, what does that mean for AI investments, deployment strategies, and the broader competitive landscape? Here’s our perspective. DeepSeek’s Approach to AI Training:Optimizing Performance Without Inflating Costs DeepSeek, a Hangzhou-based AI company, is rethinking how models are trained. Instead of relying on massive compute-heavy infrastructures, its models leverage reinforcement learning (RL) and Mixture-of-Experts (MoE) architectures to improve performance while reducing computational demands. Why does this matter? Because for years, the prevailing belief has been that bigger is better—that increasing the size of AI models and throwing more compute at them is the only way to drive better performance. DeepSeek’s method challenges this assumption by showing that architectural efficiency can be just as critical as raw computing power. Market Response: A New Contender Enters the Field When DeepSeek r1 launched in December 2024, it immediately sparked discussion. Stock fluctuations among major AI players this past week reflected the market’s uncertainty—is this a true disruption, or just another competitor entering an already crowded space? What’s clear is that DeepSeek’s focus on cost efficiency is tapping into an industry-wide concern. AI adoption is expanding beyond tech giants to businesses across industries, and with that comes an urgent need for more affordable, scalable AI solutions. DeepSeek isn’t just offering an alternative—it’s fueling a broader conversation about how AI should be built and deployed in the future. Strategic Considerations for Technology Leaders One of DeepSeek’s biggest advantages is its ability to deliver high performance at a lower cost. For enterprises that have struggled with the high price tag of AI adoption, this signals a potential shift. Historically, organizations investing in AI needed substantial infrastructure and compute resources—barriers that limited access to only the largest, most well-funded players. DeepSeek’s model suggests a different future, where AI solutions could become more broadly accessible without requiring major infrastructure overhauls. AI Efficiency: The Next Battleground? DeepSeek’s emergence highlights a growing industry-wide shift away from brute-force scaling toward intelligent optimization. Established players like OpenAI and Google are being pushed to explore new ways to improve efficiency as AI adoption scales globally. Companies like Writer and Liquid.ai are also joining this trend, working to develop models that balance power and efficiency without demanding excessive compute resources. This signals an industry-wide recognition that efficiency—not just raw power—may be the real competitive differentiator in AI’s next phase. Navigating the Challenges: Data Privacy and Security DeepSeek’s Chinese origins introduce important security and regulatory considerations. Enterprises that operate under GDPR, CCPA, or other global privacy regulations will need to carefully evaluate how DeepSeek’s models fit into their compliance frameworks. For companies considering DeepSeek’s AI, risk mitigation strategies should include: Running models in secure, isolated environments to ensure compliance with internal security policies. Evaluating the transparency of AI vendors to ensure responsible data usage. Assessing long-term regulatory implications when deploying models built outside of their primary market. The Future of AI is Changing—How Will Enterprises Respond? DeepSeek’s AI innovations aren’t just about a new player entering the market—they’re about a broader industry shift. As cost-efficient models gain traction, organizations need to rethink how they assess AI investments, optimize infrastructure, and navigate regulatory risks. The real question now is how quickly the industry will respond. Will established players adapt to the growing demand for cost-efficient AI architectures, or will newer entrants set the pace for innovation? One thing is clear: AI’s next phase isn’t just about scale—it’s about building smarter, more accessible solutions. For a deeper dive into these trends, check out our full IDC research report. source

This IDC Blog provides an initial assessment of the potential implications of the new US administration on the worldwide Information Communication Technology (ICT) market. The global digital landscape is experiencing profound transformations, with a deepening interdependence between technology and economic growth. This convergence brings a host of uncertainties, opportunities, and challenges, further complicated by ongoing global tensions. In IDC’s Future Enterprise Resilience & Spending Survey (Wave 11, December 2024), over 30% of the IT leaders considered “the impact of geo-political factors (e.g. tariffs, export controls) on tech budgets” to be the primary risk for technology strategies and spending in the coming year. The 2024 US elections were watched with keen interest, considering the global implications of US policy. There is much speculation around the new administration’s agenda, budget priorities, shifts in policy and regulations, proposals for new programs such as the Department of Government Efficiency (DOGE), and the impact of tech leaders in positions of political influence. The second term of the Trump administration officially kicked off on January 20th and from day one the administration started enacting a series of executive orders. These changes are likely to have an impact on technology suppliers, vendors that serve US federal, state and local governments, and enterprises in the private sector. In the coming year, governments and businesses in other countries will also need to assess the implications on their technology investments and priorities. As the details of the Trump administration emerge in the coming weeks, we will be identifying significant impacts on the technology and digital landscape, particularly in the following areas: the US Government Digital Agenda, Technology Trade and Digital Supply Chain, Digital Regulation and Policy, Data Privacy and Cybersecurity, and Energy and Green Technology. Key Tech Topics to Watch in 2025 The US Government Digital Agenda In the past months, President Trump and other leaders within the incoming US administration voiced plans to reverse several initiatives of the Biden administration that impact healthcare, climate, AI and cybersecurity policies, government spending, and budget priorities. Budget negotiations are also on the horizon with the current federal government funded through March 14, 2025. Even more changes are possible depending on the impact of the Department of Government Efficiency (DOGE) and the roles for private sector advisors within specific agencies to recommend budget cuts, staff reductions and possibly reforms in disaster relief, immigration and the tax code.  The federal budget and shifting priorities will also have far-reaching impacts on US state and local governments, as well as research programs and sectors that rely heavily on federal programs and grant money, which often support investments in technological innovations. Shifting budget priorities to domestic issues could negatively impact funding for international nonprofits and foreign aid agencies which as of late, have been pursuing tech modernization. Technology Trade and Digital Supply Chain Trade policies were a key pillar of President Trump’s 2024 campaign. The incoming administration has signaled a willingness to pursue additional export controls on national security grounds, especially in advanced technology. This is considering a continued negative balance of trade in technology, which increased from -$2.18 billion in 2023 to -$2.7 billion in 2024, according to data from the U.S. Census Bureau. Upon inauguration, President Trump introduced a memorandum on “America First Trade Policy,” which directs federal agencies to address trade deficits, explore an External Revenue Service for tariffs, and assess export controls to maintain the US’s “technological edge.” Over the coming weeks, it will be important to monitor free trade agreements, bilateral trade deals, IP legislation, semiconductor supply chain policies, and more, as these will all potentially have digital impacts. Maintaining this edge in AI appears to be a priority, and work is being done in securing AI/digital supply chains. President Trump repealed former President Biden’s 2023 executive order on AI risks, stating that it hinders AI innovation (see next section). However, he has thus far maintained executive orders related to AI supply chains from the Biden administration, including one on securing energy for AI and a new AI export control framework introduced last week. This framework provides global licensing requirements, expands the Foreign Direct Product Rule to cover advanced AI chips and model weights, imposes quotas to limit their accumulation, and reshapes semiconductor trade by targeting high-performance AI technologies. These restrictions, if upheld, will have potential impacts on the global AI market and access to digital supply chains. Digital Regulation and Policy Key figures in the Trump administration have voiced support for general deregulation, considering extensive laws as inhibitors to innovation. Digital regulations that are anticipated to undergo significant changes will include data privacy (see next section), data center development, telecommunications—particularly in relation to 5G advancements—and AI. President Trump overturned former President Biden’s 2023 executive order on AI that put in place guardrails around the AI development and usage. While the new administration may reshape existing digital regulations, we anticipate that a degree of scrutiny will remain consistently in place. This week, President Trump announced “Stargate,” a $500 billion AI infrastructure initiative led by OpenAI, SoftBank, and Oracle with support from major investors including MGX (Abu Dhabi’s AI-focused fund) and technology partners Microsoft, Nvidia, and Arm Holdings. The stated goal of Stargate is to build advanced data centers and virtual infrastructure in the U.S. and continue the US lead in AI innovation. The first datacenter is reported to be under construction in Abilene, Texas.  The move could create more AI jobs and create more AI-ready infrastructure to advance AI development and deployment. The delivery of these large-scale datacenters requires resources, and the Stargate team is complex with multiple high-powered stakeholders, so it will be important to watch the timeline for build out and completion. It is also important to consider that AI innovation will require participation from start-ups and smaller innovators beyond the Stargate members and global competitiveness will require advancements in AI research, talent development, and responsible AI guardrails.  With the nomination of Commissioner Andrew Ferguson as chair of the Federal Trade Commission (FTC or Commission) and Gail Slater to

Managing customer data has never been more important – or more complex. Organizations are grappling with the need to not only consolidate vast amounts of customer data but to use it as a foundation for driving personalized, omnichannel customer experiences. At the heart of this transformation is the Customer Data Platform (CDP) – a technology that enables organizations to unify fragmented data and profiles, build segments, and use AI, orchestration and activation capabilities to deliver exceptional customer engagement and drive alignment between marketing, sales, customer success and other functional teams. CDPs: Backbone of Data-Driven Engagement Whether you are operating in B2C or B2B markets, customer experience (CX) matters more than ever. It is a strong driver of financial growth and organizational outcomes and sets leaders apart from followers. B2C brands engage with customers, who often switch between channels, through multiple touchpoints and modalities. A successful CDP should allow businesses to deliver cohesive, personalized experiences across all these channels, ensuring that a customer’s journey is consistent regardless of where it begins or ends—whether in-store, in contact center, in-field, online, or on social media. Effective omnichannel orchestration drives higher engagement and reduces friction in customer journey, which is particularly important in B2C sectors like retail, travel, financial services, and hospitality. B2B brands are always looking for opportunities to drive growth and differentiation for their products and services as they lean into the shift towards consumer-like purchasing behavior. B2B buyers are demanding omnichannel journey experience, clear understanding – not of just their needs, but also the role they play in the buying group – and experimentation with new channels, especially digital. Firms are adopting CDP technologies that can unify and activate individual data across accounts and opportunities and navigate multi-stakeholder, non-linear acquisition and retention cycles to serve their B2B customers. Evaluating B2B and B2C CDPs: Tailoring Your Approach While the foundational goals of CDPs—data unification, analytics and AI, and engagement—are consistent across industries, their applications in B2B and B2C context differ. In B2C environments, CDPs must handle vast amounts of customer data generated by millions of interactions daily. The emphasis is on scale, speed, and dynamic personalization. B2C CDPs need to enable real-time marketing interactions that adapt instantly to customer behaviors, ensuring relevance and impact. Key success metrics often include customer lifetime value, conversion rates, and engagement levels. Conversely, B2B CDPs are optimized for precision and alignment with longer, more complex sales cycles. These platforms focus on account-based marketing (ABM), lead scoring, and multi-touch attribution, providing insights that enable sales and marketing teams to work seamlessly together. Integration with enterprise systems and the ability to support high-value, multi-stakeholder accounts are critical. These customer and buyer trends have pushed vendors to provide integrated CDPs with functionality ranging from data unification and management, analytics and AI to activation. There has been ongoing market deliberations between packaged CDP vendors who provide integrated all-in-one solution, but also emphasize interoperability, extensibility, and modularity, and composable CDP vendors who offer buyers the flexibility to select and assemble individual CDP functional components. Even between these two informal classification of CDP vendors, there is overlap of functionality, workflows, systems and architecture approaches. Overall, the CDP market continues to be diverse and there is some level of confusion for buyers. Buyers must carefully consider not only CDPs, but how their selected solution will integrate with other MarTech (marketing technology) and enterprise investments. Growing Interest in CDPs From IT and Data Personas As CDPs evolve, their appeal is extending beyond traditional marketing users. Today, data management and IT leaders and users are emerging as additional stakeholders in CDP evaluation decisions. For these personas, the focus is on ensuring that the CDP integrates with broader data ecosystems, particularly cloud data warehouses and enterprise analytics platforms. CDPs that offer robust APIs, native integrations, zero-copy and zero-ETL approach, and support for modern data architectures are gaining traction as businesses prioritize interoperability and scalability. Additionally, data and IT teams are increasingly involved in evaluating the security, privacy, compliance, and governance features of CDPs. As regulations become more stringent and as customers demand transparency and trust in how their data is being used, handled and protected, CDPs that address these challenges while offering hyper personalization are becoming essential in an organization’s marketing and CX technology stack and for brands to differentiate themselves from competitors. Announcing the IDC MarketScape: Customer Data Platforms To bring clarity to this rapidly evolving market and for buyers, IDC has released two MarketScape reports that help you understand and evaluate how these vendors stack up against capabilities and strategy criteria. The CDP market is constantly evolving, with vendors that vary in size, expertise, and geographic focus. Key Findings: AI and Analytics Lead the Way: Platforms incorporating AI for predictive analytics, audience segmentation, lead scoring, journey optimization, churn prevention and related use cases are delivering value for organizations. Interest and use of Generative AI is rising: Evaluate how GenAI capabilities within CDP tooling and workflows will make it easier for non-technical users in terms of productivity and data literacy for users and drive better personalization of content and engagements. Go beyond structured data sources: Consider how unstructured and semi-structured data can be transformed into consistent attributes, enrich it with identity services and further augment customer profiles for broader marketing, sales, customer service, etc. use cases. Privacy and Governance as a Feature, not a Hurdle: Vendors that embed privacy, consent management and compliance tools directly into their platforms are helping businesses build trust while delivering personalization. Real-Time Engagement is Non-Negotiable: CDPs excel in enabling real-time data activation to meet customers where they are, instantly and effectively, especially in B2C settings, to drive higher engagement rates and meet continuously evolving customer expectations. Omnichannel activation is key: Weigh how CDPs will help to simplify tooling, spend and complexity associated with campaign execution across channels within your existing or planned MarTech stack. Playbooks and Use Case templates: Prioritize CDPs that offer templates, schemas, or playbooks specific to B2C or B2B functions and use cases to streamline implementation and adoption. Value Measurement: There

As 2024 comes to a close, organizations across industries are preparing for change in 2025. Technology is advancing rapidly with investments being prioritized, use cases being evaluated, and employees being primed for the changes on the horizon. 2024 was clearly the year of Artificial intelligence (AI). It comes as no shock that within the coming year we saw more AI. However, we would need some advancements in areas such as autonomous agents. With this looming pivot around AI, the ability for business functions, teams, and stakeholders to orchestrate data seamless to make better informed decisions will be the dividing line between success and failed proof of concepts or investments. In this environment, the experience-orchestrated business (X-O) is a transformative approach that leverages AI and generative AI (GenAI) to create interconnected, data-driven experiences for all stakeholders. This concept is crucial as it enables organizations to deliver enhanced value and differentiated outcomes in a competitive market. AI and GenAI technologies play a pivotal role in this transformation by: Optimizing processes Automating tasks Breaking down data silos These advancements allow businesses to align actions with desired outcomes, ensuring that investments yield meaningful results. In an X-O business, data and insights are embedded in daily operations, fostering a connected ecosystem that benefits employees, customers, and partners alike. This shift not only improves efficiency but also drives innovation and growth, making it essential for organizations aiming to thrive in the digital age. Overcoming Challenges in Transitioning to an Experience-Orchestrated Business Transitioning to an experience-orchestrated (X-O) business is a complex endeavor that involves several significant challenges. One of the primary hurdles is transforming existing business operations. This requires a comprehensive roadmap, the establishment of new metrics, and the integration of advanced technologies like AI and GenAI. Organizations must be prepared to overhaul their processes and systems to align with the goals of an X-O business. Stakeholder alignment is another critical challenge. Internal and external stakeholders often have different perspectives, success metrics, and goals. Achieving a unified vision and ensuring that all parties are working towards common objectives is essential for the success of an X-O business. This alignment and orchestration requires continuous communication and collaboration to align expectations and outcomes. Data silos present a significant barrier to the seamless flow of information necessary for an X-O business. Many organizations struggle with fragmented data environments, which hinder their ability to unify customer and operational data. Breaking down these silos and ensuring data accessibility and integration across all functions is crucial for deriving actionable insights and delivering cohesive experiences. Employee resistance to change is another major obstacle. The shift to an X-O business involves adopting new technologies and processes, which can be met with apprehension and resistance from employees. Educating and engaging employees about the benefits and value of becoming an X-O business is vital. Addressing their concerns and demonstrating how these changes can enhance their roles and contribute to the organization’s success will help mitigate resistance and foster a culture of innovation and adaptability. Steps to Implement Experience-Orchestrated Applications Establish Metrics Begin by defining clear metrics that align with your organization’s goals. These should measure both internal and external stakeholder experiences. Metrics like customer satisfaction, employee engagement, and operational efficiency are crucial. Regularly review these metrics to ensure they reflect the evolving needs of your stakeholders. Invest in Technology Invest in AI-enabled technologies that support experience orchestration. This includes predictive analytics, machine learning, and generative AI. These technologies will help automate tasks, optimize workflows, and provide actionable insights. Ensure your technology stack is integrated and scalable to adapt to future needs. Educate Stakeholders Educate all stakeholders about the benefits and functionalities of experience-orchestrated applications. This includes training sessions for employees, informational meetings for executives, and collaborative workshops with external partners. Clear communication will help mitigate resistance and adopt a culture of innovation. Foster Collaboration Encourage collaboration across departments and with external partners. Break down data silos to ensure seamless information flow. Use collaborative tools and platforms to facilitate communication and data sharing. This will help in creating a unified approach to delivering exceptional experiences. By following these steps, organizations can effectively become an experience-orchestrated business, driving value and differentiation in a competitive market. The Future of Experience-Orchestrated Business X-O business models offer transformative benefits, including enhanced stakeholder engagement, streamlined operations, and improved decision-making. Embracing this transformation is crucial for staying competitive in an AI-driven world. Organizations must prioritize outcomes over outputs, leveraging AI to create interconnected experiences. The journey to becoming an experience-orchestrated business is challenging but essential for long-term success. Start by assessing your digital maturity, aligning metrics, and fostering a culture focused on value creation. Now is the time to act and lead your organization into the future of X-O business. source

In a world where change is constant and opportunities are often hidden in plain sight, organizations must navigate a maze of challenges while identifying the pathways that lead to growth. Staying competitive requires not just data but meaningful insights to inform decisions and shape strategies. IDC’s recent research highlights how businesses are increasingly leveraging AI and other advanced technologies to stay ahead. The market for AI platforms, for instance, saw impressive growth in 2023, with revenue expanding by 44.4%, reflecting the surge in AI adoption across industries​. The Power of Actionable Insights Actionable insights have become the key for businesses to stand out and lead with purpose. These insights are more than just data—they are the catalysts that drive strategic decisions, enabling organizations to identify opportunities and address challenges with precision and agility. IDC’s research emphasizes the growing role of market intelligence in decision-making, with Strategic Market Insights (SMI) tools offering businesses access to comprehensive data, trends, and forecasts that are critical for making informed choices. IDC’s Rapid Modules, such as Barometer and Analyst Pulse, provide businesses with quick access to proprietary data, insights, and their very own IDC analyst panel. These tools offer a valuable lens for tracking the pace of AI adoption and understanding market dynamics. What makes these insights particularly powerful is the credibility of the research behind them. IDC has been recognized as the Analyst Firm of the Year for the fifth consecutive year by The Institute of Influencer & Analyst Relations (IIAR). This recognition highlights IDC’s reputation for thorough analysis, strategic thinking, and expertise across areas like AI services, cybersecurity, digital commerce, and emerging technologies such as generative AI. Addressing Key Challenges for Long-Term Success As companies embrace actionable insights, they must also address key challenges—such as digital security, technical debt, and the evolving role of AI. These challenges must be recognized and tackled head-on to stay ahead of the curve and set the foundation for sustainable success. Let’s take a closer look at how these issues impact strategic planning. Expanding Digital Security FrontiersWith the sophistication of cyberattacks increasing, safeguarding data has never been more important. IDC’s research suggests integrating AI into security systems to protect sensitive information and maintain customer trust. AI can enhance security measures, detecting anomalies and mitigating risks in real time, making it an essential part of any security strategy. Managing Technical DebtAdopting new technologies often leads to the accumulation of technical debt, creating inefficiencies. IDC stresses the importance of addressing these issues to maintain agility and drive innovation. Organizations must streamline processes, update legacy systems, and integrate new technologies seamlessly to stay competitive in an ever-changing market. Monetizing AIWhat was once considered hype, generative AI is now a crucial business tool. IDC reports that nearly half of organizations deploying generative AI in production have selected AI platforms. This shift creates new opportunities to explore revenue streams, enhance product offerings, and adjust business models to align with evolving market demands. Unlocking the Full Potential of Strategic Insights As businesses continue to adopt data-driven strategies, it becomes clear that insights are the true differentiator. By embedding these insights into every level of their operations, organizations can gain a competitive advantage, accelerate growth and ensure long-term sustainability. IDC’s research shows that businesses leveraging strategic insights, particularly through AI and advanced analytics, are better positioned to respond to market shifts and align offerings with demand in real time. Furthermore, organizations increasingly rely on third-party data and AI to enhance their insights. This enables more effective decision-making through predictive analytics that drive performance. As AI adoption accelerates, IDC forecasts a 50.9% compound annual growth rate (CAGR) for cloud-based AI platforms over the next five years. This shift to cloud platforms not only increases operational efficiency but also enables businesses to scale securely and adapt swiftly, reinforcing the value of strategic insights as guiding forces in an organization’s long-term strategy. Embracing Strategic Leadership To stay ahead, organizations must move beyond simply reacting to change. They must leverage tools like IDC’s Strategic Market Insights and thought leadership to lead proactively. By embracing these insights, companies can maintain a neutral and unbiased view of the market, positioning themselves to foresee change, allocate resources effectively, and navigate an increasingly digital landscape with resilience. Building a Future-Ready Roadmap Strategic planning has never been more crucial. It’s not just about keeping up—it’s about staying agile, spotting new opportunities, and making smarter decisions at every turn. To get there, businesses need to embed actionable insights into their day-to-day operations. This goes beyond simply collecting data—it’s about transforming that data into actionable perspectives and insights, viewed from multiple angles. IDC’s research makes it clear: the organizations that leverage strategic insights, particularly through AI and advanced analytics, are the ones poised for success. source