Data and its free flow between service, sales, marketing, and commerce applications are foundational to the creation of digital customer experiences. Recent research by TechTarget’s Enterprise Strategy Group delved into the data management and platforms challenges organizations are facing in pursuit of customer experience (CX) goals, as well as subsequent impacts on technology spending in this area.
Business Applications & End-user Computing
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Customer satisfaction is one of the keys to retaining loyal consumers who repeatedly purchase goods and services as well as recommend the business to consumers. Strong customer experience (CX) programs support customer satisfaction by ensuring their interactions with the brand are smooth, timely, and relevant at every stage. Recent research by TechTarget’s Enterprise Strategy Group shows that the responsibility for executing CX strategies has begun to shift from a marketing function to a more holistic initiative within the customer service domain.
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The artificial intelligence movement over the last several years has been enabled by the exponential growth in computing power, data, algorithms, and use cases. As AI is increasingly integrated across industries, AI infrastructure decisions have become pivotal to support widespread deployment as well as the need to satisfy resource-heavy AI workloads. Recent research by TechTarget’s Enterprise Strategy Group found that a range of factors are now top of mind for executives shaping their AI strategies.
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In an era where the effective use of AI technology can mean sinking or swimming in highly competitive business waters, organizations are laser-focused on making sure their AI models are fine-tuned and well trained to enhance their operations. But training AI algorithms on real customer data can risk compliance and privacy violations. Recent research by TechTarget’s Enterprise Strategy Group examined how organizations are using synthetic data to avoid data governance problems with AI training and whether this is delivering the anticipated advantages.
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As businesses across the globe pursue AI to revolutionize their businesses, the powerful infrastructure required to support these innovations and transformations is driving an increased focus on responsible purchase strategies. Recent research by TechTarget’s Enterprise Strategy Group revealed that sustainability concerns are taking center stage as organizations grow their AI infrastructure initiatives and footprints.
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The hype around AI transformation has infiltrated business lines across all areas of organizations, and with freely available generative AI (GenAI) technology, anyone can take the opportunity to explore AI’s possibilities. Recent research by TechTarget’s Enterprise Strategy Group closely examined the actions of formal stakeholders for AI initiatives today and reached some nuanced conclusions about who should be involved in these decisions and when.
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AI has become a key investment for organizations as they seek to foster innovation and gain a competitive edge. But selecting and deploying the right AI solution is still quite challenging, often entailing substantial initial and ongoing investments of time, people, and money. Recent research by TechTarget’s Enterprise Strategy Group sought to understand the time-to-value situation for AI projects today and what this might say about innovation in the AI market in general.
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Organizations have been broadly and enthusiastically adopting initiatives involving artificial intelligence, and the maturity of those initiatives within business operations is on the rise. Recent research by TechTarget’s Enterprise Strategy Group found two key drivers of these trends: anxieties that businesses will miss out on the advantages of generative AI (GenAI) and the increasing focus of vendors and partners on simplifying their products and services.
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Discover what’s trending on our network to engage IT buyers in market now and improve marketing and sales effectiveness. This report covers trending areas of interest across 240+ IT markets over the last 6 months (April 2023 – September 2023) in five (5) regions across the TechTarget & BrightTALK network: WW, NA, EMEA, APAC, LATAM.
In this report you will find:
• The top 20 broad technology markets driving the most activity in the past 6 months. Activity data can help show where audience research is growing or declining and therefore help reinforce which markets are on the rise or declining.
• The top 25 granular topics growing the most across the TechTarget and BrightTALK network in the last 6 months. This gives insight into the content areas that are on the rise right now to leverage in your conversations.Already an Enterprise Strategy Group client? Log in to read the full report.
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As AI continues its meteoric rise into business and IT environments, organizations are rapidly assembling or accelerating strategies to support AI technologies across every applicable area. Unlike niche technologies that impact only certain processes or personnel, AI has wide-ranging potential to transform entire businesses, IT environments, and associated teams. In turn, AI strategies must be multi-pronged efforts that properly align business objectives with AI initiatives and expectations, which requires thorough participation from stakeholders across the organization. The underlying infrastructure and other supportive elements must be fully capable of supporting that tandem strategy.
While many organizations are consistent in their efforts to build AI strategies, the components and direction of those strategies often vary. To assess the evolving AI landscape and the infrastructure that supports it, TechTarget’s Enterprise Strategy Group surveyed 375 data and IT professionals in North America (US and Canada) responsible for strategizing, evaluating, purchasing, and/or managing infrastructure specifically supporting AI initiatives for their organization. This study sought to answer the following questions:
- What are the primary business objectives for implementing AI? How long does it take for organizations to start seeing value from AI initiatives?
- What are the top challenges organizations encounter when implementing AI?
- What individuals or teams influence decision making related to infrastructure used to support AI initiatives? Which of these has the most influence on final decisions?
- How are organizations planning to address skills gaps related to the selection, implementation, and management of infrastructure supporting AI initiatives?
- In which physical locations do organizations primarily deploy their AI infrastructure? What are the top factors that influence the choice of these locations? Are AI environments mostly centralized, mostly decentralized, or an even mix of both?
- What capabilities of AI infrastructure are most important?
- Are organizations using internal resources, third-party resources, or both to manage their AI infrastructure?
- How important is sustainability and environmental responsibility when selecting AI infrastructure? How important is a vendor’s stance on these factors when making purchase decisions for AI infrastructure?
- What types of data do organizations use to build and train AI models and algorithms? What steps do organizations take to ensure accuracy in the data used for building and training these models?
- How do organizations handle the movement of the large amounts of data required to support AI initiatives? What challenges are involved with this process?
- How are organizations using synthetic and third-party data to support AI model training?
- How are organizations using generative AI (GenAI)? What challenges are they encountering?
- To what extent are developers leveraging AI infrastructure resources? How do developers access these resources?
- How do organizations measure the success and effectiveness of AI initiatives?
- What is AI’s impact on employee productivity, processes, workflows, competitiveness, and other factors?
Survey participants represented a wide range of industries, including financial, manufacturing, retail/wholesale, and healthcare, among others. For more details, please see the Research Methodology and Respondent Demographics sections of this report.
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Organizations across markets and geographies are expecting generative artificial intelligence (GenAI) to disrupt and transform their business processes. Recent research by TechTarget’s Enterprise Strategy Group revealed some interesting findings when it comes to customer experience (CX) use cases for this buzzy technology.
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