Data Management, Analytics & AI

Organizations investing in AI are implementing comprehensive value assessments both during deployment and after launch. While this strategy strives to ensure AI solutions continue to align to business objectives and deliver on their promised value, the resulting sprawl of performance and value metrics may be overcomplicating the process of finding full-stack AI solutions. Recent research by Informa TechTarget’s Enterprise Strategy Group revealed that teams may have trouble finding satisfactory AI platforms as their requirements sprawl.

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Organizations are continuing a flurry of investments in AI, often spurred by ongoing enthusiasm around generative AI initiatives and their potential to radically improve operational efficiency and productivity. Recent research by Informa TechTarget’s Enterprise Strategy Group revealed that teams will sometimes find themselves paradoxically having to apply some of these investments to specific issues introduced by AI deployment.

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Against a backdrop of AI excitement and continuous rollouts of new large language models, organizations are contending with the critical balance of innovation and responsible AI, including strategies for data privacy, bias mitigation, compliance, ethical usage, and more. Recent research by Informa TechTarget’s Enterprise Strategy Group revealed that, although most organizations are making progress in ensuring AI is used ethically and responsibly, different industries vary widely on their approaches.

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Even moderate AI usage within an organization warrants a responsible AI strategy supported by technical stakeholders and foundational policies, but recent research by Informa TechTarget’s Enterprise Strategy Group found that certain teams generally have more comprehensive practices for responsible AI than others. Using those organizations as a model for responsible AI development can help other teams get their operations in order as they roll out more initiatives that expose the business to greater risk in the event of unethical or noncompliant AI use.

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Digital transformation (DX) initiatives are continuing, but they are beginning to take on a new shape with the arrival of widespread AI deployments. Recent research by Informa TechTarget’s Enterprise Strategy Group uncovered some of the key practices of organizations with mature DX initiatives, which those in the earlier stages of digital transformation can learn from to understand where IT pioneers are headed.

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Enterprises (1,000+ employees) are turning to generative AI (GenAI) for wide-ranging strategic benefits, but they’re far more likely to encounter certain challenges than large midmarket (500 to 999 employees) in these endeavors, according to research by Informa TechTarget’s Enterprise Strategy Group. A recent study found that although both large and smaller organizations engage with partners regularly to overcome GenAI project challenges, enterprise-size firms tend to need vendors’ support in specific crucial areas in their pursuit of large-scale transformation.

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All major industry verticals are moving forward with generative AI (GenAI) deployments to capture competitive differentiation from cutting-edge technology. Since skill sets and resources for development vary widely from industry to industry, and even organization to organization, many firms are active in partnering with outside vendors and service providers for technology deployment, strategy guidance, and other expertise pertaining to GenAI. Recent research by Informa TechTarget’s Enterprise Strategy Group revealed some interesting findings when it comes to how different industries tackle GenAI initiatives and subsequent third-party engagements in support of those projects.

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The proliferation of customer-centric systems, tools, and applications within businesses is daunting, especially when undermining goals of operational speed, agility, and efficiency. This extends to customer service (CS) operations, which increasingly supports overarching customer experience initiatives. Recent research by Informa TechTarget’s Enterprise Strategy Group explored how organizations harness the power of generative AI (GenAI) to mitigate the potentially negative effects of having distributed and/or siloed CS applications and tools throughout a business.

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Customer experience (CX) strategies are often at the heart of competitive differentiation today. From personalized experiences and top-notch customer service (CS) to ensuring trust and process efficiency, many businesses recognize the importance of supercharging CX practices to maintain customer loyalty and improve customer acquisition. Recent research by Informa TechTarget’s Enterprise Strategy Group investigated how organizations view and act on the opportunity to augment and improve CX strategies by using cutting-edge AI technology that drives automation and other improvements.

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