Speaking at the Gartner IT Infrastructure, Operations & Cloud Strategies Conference in Sydney, Paul Delory, VP Analyst at Gartner said, “In the current economic climate, the biggest problem companies face in 2023 may not be IT infrastructure. I&O teams, however, will be impacted by economic and geopolitical forces and will have a vital role to play in ameliorating their effects.”

Delory continued, “This won’t be a year to realize grand ambitions, but it marks a moment to refocus, retool and rethink your infrastructure. In every crisis lies opportunity, and in this case, the chance to make positive changes that may be long overdue.”

According to the Stamford, Conn. research firm, the top four cloud, data center and edge infrastructure trends include the following:

Trend 1: Cloud Teams Will Optimize and Refactor Cloud Infrastructure

Public cloud usage is almost universal, but many deployments are ad hoc and poorly implemented, says Gartner. I&O teams have an opportunity this year to revisit hastily assembled or poorly architected cloud infrastructure to make it more efficient, resilient and cost-effective.

The focus of refactoring cloud infrastructure should be on optimizing costs by eliminating redundant, overbuilt or unused cloud infrastructure; building business resilience rather than service-level redundancy; using cloud infrastructure as a way to mitigate supply chain disruptions; and modernizing infrastructure. According to Gartner, 65% of application workloads will be optimal or ready for cloud delivery by 2027, up from 45% in 2022.

Trend 2: New Application Architectures Will Demand New Kinds of Infrastructure

I&O teams are continually challenged to meet new and growing demands with new types of infrastructure — including edge infrastructure for data-intensive use cases, non-x86 architectures for specialized workloads, serverless edge architectures and 5G mobile service. Gartner predicts 15% of on-premises production workloads will run in containers by 2026, up from less than 5% in 2022.

I&O professionals must evaluate alternative options with care, focusing on their ability to manage, integrate and transform in the face of constraints on time, talent and resources. “Don’t revert to traditional methods or solutions just because they’ve worked well in the past,” said Delory. “Challenging periods are times to innovate and find new solutions to meet business demands.”

Trend 3: Data Center Teams Will Adopt Cloud Principles On-Premises

Data centers are shrinking and migrating to platform-based colocation providers. Combined with new as-a-service models for physical infrastructure, this can bring cloud-like service-centricity and economic models to on-premises infrastructure.

According to Gartner, 35% of data center infrastructure will be managed from a cloud-based control plane by 2027, from less than 10% in 2022. I&O professionals should focus this year on building cloud-native infrastructure within the data center; migrating workloads from owned facilities to co-location facilities or the edge; or embracing as-a-service models for physical infrastructure.

Trend 4: Skills Growth: Top Priority for Successful Organizations

Lack of skills remains the biggest barrier to infrastructure modernization initiatives, with many organizations finding they cannot hire outside talent to fill these skills gaps. IT organizations will not succeed unless they prioritize organic skills growth.

I&O leaders must make operations skills growth their highest priority this year. Encourage I&O professionals to take on new roles as site reliability engineers or subject matter expert consultants for developer teams and business units. Gartner predicts 60% of data center infrastructure teams will have relevant automation and cloud skills by 2027, up from 30% in 2022.

The post These Four Trends Are Shaping the Future of IT Infrastructure appeared first on My TechDecisions.

“The need to deliver provable value to the organization at scale is driving these trends in D&A,” said Gareth Herschel, VP Analyst at Gartner, in a statement. “Chief data and analytics officers (CDAOs) and D&A leaders must engage with their organizations’ stakeholders to understand the best approach to drive D&A adoption. This means more and better analysis and insights, taking human psychology and values into account.”

Gartner analysts presented the top 10 D&A trends that business and IT leaders must engage and incorporate into their D&A strategy at the 2023 Gartner Data & Analytics Summit.

Trend 1: Value Optimization

Most D&A leaders struggle to articulate the value they deliver for the organization in business terms. To achieve value optimization from an organization’s data and artificial intelligence (AI) portfolio, specific competencies such as value storytelling, value stream analysis, investment ranking and measuring business outcomes are required. D&A leaders should build clear links between their projects and the organization’s mission-critical priorities.

Trend 2: Managing AI Risk

The growing use of AI has exposed companies to new risks such as ethical risks. Managing AI risks is not only about being compliant with regulations. Effective AI governance and responsible AI practices are also critical to building trust among stakeholders and catalyzing AI adoption and use.

Trend 3: Observability

Observability is a characteristic that allows the D&A system’s behavior to be understood and allows questions about their behavior to be answered.

“Observability enables organizations to reduce the time it takes to identify the root cause of performance-impacting problems and make timely, cost-effective business decisions using reliable and accurate data,” said Herschel. “D&A leaders need to evaluate data observability tools to understand the needs of the primary users and determine how the tools fit into the overall enterprise ecosystem.”

Trend 4: Data Sharing Is Essential

Data sharing includes sharing data both internally (between or among departments or across subsidiaries) and externally (between or among parties outside the ownership and control of your organization). Organizations can create “data as a product,” where D&A assets are prepared as a deliverable or shared product.

“Data sharing collaborations, including those external to an organization, increase data sharing value by adding reusable, previously created data assets,” said Kevin Gabbard, senior director, analyst at Gartner, in a statement. “Adopt a data fabric design to enable a single architecture for data sharing across heterogeneous internal and external data sources.”

Trend 5: D&A Sustainability

According to Gartner, it is not enough for D&A leaders to provide analysis and insights for enterprise ESG (environmental, social, and governance) projects. D&A leaders must optimize their own processes for sustainability improvement. D&A and AI practitioners are becoming more aware of their growing energy footprint. As a result, a variety of practices are emerging, such as the use of renewable energy by (cloud) data centers, the use of more energy-efficient hardware, and the usage of small data and other machine learning (ML) techniques.

Trend 6: Practical Data Fabric

Trend 7: Emergent AI

ChatGPT and generative AI are the vanguard of the coming emergent AI trend. Emergent AI will change how most companies operate in terms of scalability, versatility and adaptability. The next wave of AI will enable organizations to apply AI in situations where it is not feasible today, making AI ever more pervasive and valuable.

Trend 8: Converged and Composable Ecosystems

Converged D&A ecosystems design and deploy the D&A platform to operate and function cohesively through seamless integrations, governance and technical interoperability. An ecosystem’s composability is delivered by architecting, assembling and deploying configurable applications and services.

With the right architecture D&A systems can be more modular, adaptable and flexible to scale dynamically and be more streamlined to meet the growing and changing business needs and enable evolution as the business and operating environment inevitably change.

Trend 9: Consumers Become Creators

The percentage of time users spend in predefined dashboards will be replaced by conversational, dynamic and embedded user experiences that address specific content consumers’ point-in-time needs.

Organizations can expand the adoption and impact of analytics by giving content consumers easy to use automated and embedded insights and conversational experiences they need to become content creators.

Trend 10: Humans Remain the Key Decision Makers

Not every decision can or should be automated. D&A groups are explicitly addressing decision support and the human role in automated and augmented decision making.

“Efforts to drive decision automation without considering the human role in decisions will result in a data-driven organization without conscience or consistent purpose,” said Herschel. “Organizations’ data literacy programs need to emphasize combining data and analytics with human decision-making.”

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The post Gartner’s Top 10 Data & Analytics Trends for 2023 appeared first on My TechDecisions.

“The generative AI frenzy shows no signs of abating,” says Frances Karamouzis, distinguished VP analyst at Gartner, in a statement. “Organizations are scrambling to determine how much cash to pour into generative AI solutions, which products are worth the investment, when to get started and how to mitigate the risks that come with this emerging technology.”

The poll was conducted among 2,544 respondents as part of a Gartner webinar series in March and April 2023 discussing the enterprise impact of ChatGPT and generative AI. Gartner cautions the results of the poll do not represent global findings nor the market as a whole.

Benefits of Generative AI Outweigh the Risks

The Gartner poll found that 68% of executives believe that the benefits of generative AI outweigh the risks, compared with just 5% that feel the risks outweigh the benefits. However, executives may begin to shift their perspective as investments deepen.

“Initial enthusiasm for a new technology can give way to more rigorous analysis of risks and implementation challenges,” says Karamouzis. “Organizations will likely encounter a host of trust, risk, security, privacy and ethical questions as they start to develop and deploy generative AI.”

Read Next: ChatGPT and Generative AI in the Workplace

Customer Experience is the Primary Focus of AI Investments

Despite ongoing economic headwinds, only 17% of executives indicated cost optimization as the primary purpose of generative AI investments. Customer experience was the most common primary focus of investments, cited by 38% of respondents.

As organizations begin experimenting with generative AI, many are starting with use cases such as media content improvement or code generation. While these efforts can be a strong initial value-add, generative AI has vast potential to support solutions that augment humans or machines and autonomously execute business and IT processes, according to Gartner.

“Autonomous business, the next macrophase of technological change, can mitigate the impact of inflation, talent shortages and even economic downturns,” says Karamouzis. “CEOs and CIOs that leverage generative AI to drive transformation through new products and business models will find massive opportunities for revenue growth.”

The post ChatGPT, Generative AI Prompt Increase in AI Investment appeared first on My TechDecisions.

The analyst firm published a Q&A featuring Avivah Litan, a vice president analyst, who says a new class of AI trust, risk and security management tools (AI TRiSM) need to be developed to help organizations manage data and process flows between users and providers of those AI models.

However, there are currently no tools on the market that provide users with those privacy assurances or effective content filtering that help prevent errors, hallucinations, copyrighted materials or confidential information, Litan says.

Generative AI models–while potentially revolutionary–are far from perfect and are prone to mistakes, including factual errors and off-base responses. In addition, there is a growing trend of these generative AI tools being used for malicious purposes, including cyberattacks, deepfakes and more.

In a recent example, an AI-generated image of Pope Francis wearing a fashionable white puffer jacket went viral on social media,” Litan says in Gartner’s published article. “While this example was seemingly innocuous, it provided a glimpse into a future where deepfakes create significant reputational, counterfeit, fraud and political risks for individuals, organizations and governments.”

In addition to well-known data privacy and copyright issues associated with these AI models, Litan calls out more advanced cybersecurity concerns, saying providers of AI models don’t provide users with the tools they  need to audit all the security control sin place.

“The vendors also put a lot of emphasis on “red teaming” approaches,” Litan says. “These claims require that users put their full trust in the vendors’ abilities to execute on security objectives.”

Set policies, monitor, and potentially block ChatGPT

To deal with these risks, organizations should establish a governance and compliance framework for enterprise use of out-of-the-box solutions, and those policies should prohibit employees from asking questions that expose sensitive organizational or personal data, Litan says.

These policies could go as far as blocking unsanctioned use of ChatGPT and similar solutions and monitor event logs for violations. As of May 2023, several companies have begun blocking their users from using ChatGPT, including Apple, Amazon and Samsung.

Jason Wong, a distinguished vice president analyst at Gartner, previously told TechDecisions that organizations should establish a “center of excellence’” to bring together the activities using the technology to better understand the collective impact. While stopping short of calling for organizations to potentially block the use of ChatGPT and other AI models, Wong says IT leaders should actively monitor it usage and have an open dialogue with users rather than denying them the use of the technology outright.

However, Litan says a “prompt engineering approach” that uses tools to create, tune and evaluate prompt inputs and outputs requires additional steps to protect internal and other sensitive data used to engineer prompts on third-party infrastructure.

IT leaders should create and store engineered prompts as immutable assets which can represent vetted engineered prompts that can be safely used.

Update May 22, 2023: This article has been updated to include examples of companies blocking ChatGPT. 

The post Should IT Block the Use of ChatGPT, Generative AI Tools? appeared first on My TechDecisions.

“Hyperscale cloud providers are driving the cloud agenda,” says Sid Nag, vice president analyst at Gartner, in a statement. “Organizations today view cloud as a highly strategic platform for digital transformation, which is requiring cloud providers to offer more sophisticated capabilities as the competition for digital services heats up.”

Nag added, “Generative AI is supported by large language models (LLMs), which require powerful and highly scalable computing capabilities to process data in real-time. Cloud offers the perfect solution and platform. It is no coincidence that the key players in the generative AI race are cloud hyperscalers.”

Infrastructure-as-a-service (IaaS) Growth forecast

All segments of the cloud market are expected see growth in 2023. Infrastructure-as-a-service (IaaS) is forecast to experience the highest end-user spending growth in 2023 at 30.9%, followed by platform-as-a-service (PaaS) at 24.1%.

The Stamford, Conn. research firm also predicts that by 2026, 75% of organizations will adopt a digital transformation model predicated on cloud as the fundamental underlying platform.

“The next phase of IaaS growth will be driven by customer experience, digital and business outcomes and the virtual-first world,” said Nag. “Emerging technologies that help businesses interact more closely and in real time with their customers, such as chatbots and digital twins, are reliant upon cloud infrastructure and platform services to meet growing demands for compute and storage power.”

While cloud infrastructure and platform services are driving the highest spending growth, SaaS remains the largest segment of the cloud market by end-user spending. SaaS spending is projected to grow 17.9% to total $197 billion in 2023.

“The technology substrate of cloud computing is firmly dominated by the hyperscalers, but leadership of the business application layer is more fragmented,” said Nag. “Providers are facing demands to redesign SaaS offerings for increased productivity, leveraging cloud-native capabilities, embedded AI and composability – particularly as budgets are increasingly driven and owned by business technologists. This change will ignite a wave of innovation and replacement in the cloud platform and application markets.”

The post Worldwide Public Cloud End-User Spending to Reach Nearly $600B in 2023 appeared first on My TechDecisions.

According to Richard Addiscott, senior director analyst at Gartner, a human-centered approach to cybersecurity is essential, and must focus on people in control design. One in which, “focus[es] on people in control design and implementation, as well as through business communications and cybersecurity talent management.” Thus, he said, “[it] will help to improve business-risk decisions and cybersecurity staff retention.

Three Key Areas for an Effective Cybersecurity Program

According to Gartner, SRM leaders need to focus on three key areas to ensure an effective cybersecurity program and address related risks:

1. The role of people for security program success and sustainability
2. Technical security capabilities that provide greater visibility and responsiveness across the organization’s digital ecosystem
3. Restructuring the way the security function operates to enable agility without compromising security

Gartner also outlines the following nine trends that will have a broad impact for SRM leaders across the three key areas above:

Gartner’s Cybersecurity Trends for 2023

Trend 1: Human-Centric Security Design

Human-centric security design prioritizes the role of employee experience across the controls management life cycle. By 2027, 50% of large enterprise chief information security officers (CISOs) will have adopted human-centric security design practices to minimize cybersecurity-induced friction and maximize control adoption.

“Traditional security awareness programs have failed to reduce unsecure employee behavior,” said Addiscott. “CISOs must review past cybersecurity incidents to identify major sources of cybersecurity induced-friction and determine where they can ease the burden for employees through more human-centric controls or retire controls that add friction without meaningfully reducing risk.”

Trend 2: Enhancing People Management for Security Program

Traditionally, cybersecurity leaders have focused on improving technology and processes that support their programs, with little focus on the people that create these changes. CISOs who take a human-centric talent management approach to attract and retain talent have seen improvements in their functional and technical maturity. By 2026, Gartner predicts that 60% of organizations will shift from external hiring to “quiet hiring” from internal talent markets to address systemic cybersecurity and recruitment challenges.

Trend 3: Transforming the Cybersecurity Operating Model to Support Value Creation

Technology is moving from central IT functions to lines of business, corporate functions, fusion teams and individual employees. A Gartner survey found that 41% of employees perform some kind of technology work, a trend that is expected to continue growing over the next five years.

“Business leaders now widely accept that cybersecurity risk is a top business risk to manage – not a technology problem to solve,” said Addiscott. “Supporting and accelerating business outcomes is a core cybersecurity priority, yet remains a top challenge.”

CISOs must modify their cybersecurity’s operating model to integrate how work gets done. Employees must know how to balance a number of risks including cybersecurity, financial, reputational, competitive and legal risks. Cybersecurity must also connect to business value by measuring and reporting success against business outcomes and priorities.

Trend 4: Threat Exposure Management

The attack surface of modern enterprises is complex and creates fatigue. CISOs must evolve their assessment practices to understand their exposure to threats by implementing continuous threat exposure management (CTEM) programs. Gartner predicts that by 2026, organizations prioritizing their security investments based on a CTEM program will suffer two-thirds fewer breaches.

Trend 5: New Identity Threat & Detection Response (ITDR)

Incomplete, misconfigured or vulnerable elements in an organization can lead to a fragile identity infrastructure. By 2027, Gartner predicts filling the gaps in identity infrastructure will prevent 85% of new attacks and thereby reduce the financial impact of breaches by 80%.

“Identity fabric immunity not only protects the existing and new IAM components in the fabric with identity threat and detection response (ITDR), but it also fortifies it by completing and properly configuring it,” said Addiscott.

Trend 6: Cybersecurity Validation 

Cybersecurity validation is the process of testing how attackers can exploit any security gaps. The tools used for this are being updated to automate assessments, making them more reliable for regular testing of attack techniques, security controls and processes. Through 2026, more than 40% of organizations, including two-thirds of midsize enterprises, will rely on consolidated platforms to run cybersecurity validation assessments.

Trend 7: Cybersecurity Platform Consolidation

As organizations look to simplify operations, vendors are consolidating platforms around one or more major cybersecurity domains. For example, identity security services may be offered through a common platform that combines governance, privileged access and access management features. SRM leaders need to continuously inventory security controls to understand where overlaps exist and reduce the redundancy through consolidated platforms.

Trend 8: Composable Businesses Need Composable Security

Organizations must transition from relying on monolithic systems to building modular capabilities in their applications to respond to the accelerating pace of business change. Composable security is an approach where cybersecurity controls are integrated into architectural patterns and then applied at a modular level in composable technology implementations. By 2027, more than 50% of core business applications will be built using composable architecture, requiring a new approach to securing those applications.

“Composable security is designed to protect composable business,” said Addiscott. “The creation of applications with composable components introduces undiscovered dependencies. For CISOs, this is a significant opportunity to embed privacy and security by design by creating component-based, reusable security control objects.”

Trend 9: Boards Expand Their Competency in Cybersecurity Oversight

The board’s increased focus on cybersecurity is being driven by the trend toward explicit-level accountability for cybersecurity to include enhanced responsibilities for board members in their governance activities. Cybersecurity leaders must provide boards with reporting that demonstrates the impact of cybersecurity programs on the organization’s goals and objectives.

“SRMs leaders must encourage active board participation and engagement in cybersecurity decision making,” said Addiscott. “Act as a strategic advisor, providing recommendations for actions to be taken by the board, including allocation of budgets and resources for security.”

The post Gartner’s Top Cybersecurity Trends for 2023 appeared first on My TechDecisions.

The Stamford, Conn.-based firm’s newest IT spending forecast report suggests that IT leaders are looking to optimize spending and using emerging technologies to transform their organization’s value proposition, revenue and client interactions. ‘

That spending is largely fueled by software and IT services, which Gartner predicts will rise by 12.3% and 9.1%, respectively. The software spending increase is due to organizations helping to increase productivity automation and other software-driven initiatives, while the services increase is driven by the infrastructure-as-a-service market, which is expected to reach over 30% growth this year.

Conversely, the spending on devices will decline nearly 5% this year as consumers defer device purchases due to declining purchasing power and a lack of incentive to buy.

“CIOs face a balancing act that is evident in the dichotomies in IT spending,” says John-David Lovelock, a distinguished vice president analyst at Gartner. “For example, there is sufficient spending within data center markets to maintain existing on-premises data centers, but new spending has shifted to cloud options, as reflected in the growth in IT services.”

The 5.5% growth in IT spending comes after the company’s January forecast suggested an increase of just 2.4%, with the company citing inflation impacting consumer spending along with an otherwise steady enterprise market.

Another reason for the increased spending on IT services is the lack of skilled IT talent, Gartner says. The demand for tech talent dwarfs the supply, and that is a trend that will continue until at least 2026, the firm says.

In fact, IT spending on internal services is slowing across all industries, and enterprises aren’t keeping up with wage increases, according to Lovelock.

“As a result, enterprises will spend more money to retain fewer staff and will turn to IT services firms to fill in the gap,” Lovelock says.

The post IT Spending to Grow 5.5% This Year Due to Software, Services appeared first on My TechDecisions.

The technology is exciting and has the power to unlock new capabilities and efficiencies that any IT leader would dream of, but it should be carefully evaluated and deployed just like any other enterprise tool, says Chirag Dekate, vice president analyst at Gartner.

According to Dekate, IT leaders should avoid the headlines about generative AI because the constant barrage of news, new products and integrations can be overwhelming. It can be hard to distinguish between different products and services, especially if organizations lack internal AI expertise.

Rather than diving headfirst into generative AI, IT leaders should evaluate the risk in engaging with these emerging AI models, evaluate the data and ethics policies of different vendors and decide whether they should wait for more advanced and accurate models to come out.

According to Dekate, there are three key considerations that IT leaders should evaluate when deploying generative AI tools in their organization.

Data security

Above anything else, the consumer adoption of generative AI shouldn’t be viewed as being in the same ballpark as business adoption, as some consumer-facing tools are trained on data inputs, meaning any proprietary information or sensitive data could be accessible by a competitor.

IT leaders should disallow widespread use of consumer-facing generative AI in enterprise applications, Dekate says.

“Any query you ask or any prompt you make essentially gets subsumed into the data model that is operating behind the scenes,” Dekate says. “With the enterprise, you cannot essentially compromise your corporate IP or customer data by integrating consumer-facing APIs into your product suite.”

IT leaders should take a hard look at the data policies of generative AI providers to ensure that their proprietary data is completely isolated from the data model,

“The first question they should ask is, ‘How is my data protected?’”

Listen to the interview with Chirag Dekate in this podcast episode!

Innovation risk

Dekate’s comments to TechDecisions came just days before thousands of AI and tech leaders called on the tech industry to pause AI investments and focus on making current models safer and more trustworthy.

According to Dekate, the rapid pace of innovation in AI could have security and privacy implications.

“The biggest risk I see in the rapid pace of innovation is potential slippage in how we secure some of the underlying data ecosystems, or inadvertently create a mechanization of noise,” Dekate says.

IT leaders need to put guardrails in place so they aren’t exposed to some of those risks.

However, generative AI companies are largely being transparent in how they communicate those risks and how models are trained. For example, OpenAI says GPT-4 was trained last year and the team spent the year vetting and testing the model. While the company says GPT-4 is capable of more than GPT-3, it is still not immune to hallucinations.

That kind of transparency should give organizations a blueprint to help them decide where the technology can help them, Dekate says.

Ethics and human control

Any application of generative AI in the business world should also adhere to ethics and responsibility frameworks that keep the control with human operators. Dekate uses the example of leveraging generative AI to create a marketing campaign by converting simple text into a blog post, but that content may include errors since generative AI tools are currently not entirely trustworthy.

Any enterprise application of generative AI should include guardrails that ensure human supervision is involved and that the output of these models is at least quality checked and approved, Dekate says.

“Without the necessary ethical guardrails and without the necessary responsibility guardrails, you run the risk of mechanizing noise and potentially showing up in the headlines for all the wrong reasons,” Dekate says.

The post Three Considerations Before Deploying Generative AI Tools appeared first on My TechDecisions.

Microsoft and Google, two the biggest players in enterprise computing, are leading the charge in bringing generative AI to the workplace with Bing and Bard, respectively. However, many other tech firms are integrating OpenAI’s GPT-4 and other language models into their solutions to provide an intelligent assistant to augment their human users’ skills.

With these tools and use cases rapidly expanding, IT leaders should begin thinking about potential use cases and developing a plan to bring generative AI to their workplace, according to two Gartner analysts during a virtual press briefing on AI from the analyst firm’s Data & Analytics Summit this week in Orlando, Fla.

Generative AI is coming for the enterprise

According to Frances Karamouzis, the group chief of research for IT leaders and GTP, and a distinguished vice president analyst at Gartner, AI already exists in a wide range of enterprise tools either in the user interface or in the functionality, so enterprise IT leaders should not shy away from adopting new generative AI tools.

While there are data privacy and security risks, as well as ethical considerations, Karamouzis says enterprises simply cannot afford to be behind the curve on AI.

“The biggest risk is standing still,” Karamouzis says.

ChatGPT beat out the largest social media platforms and other popular consumer apps for reaching 1 million users first, achieving the feat in just five days. And, the chatbot is widely available and easy to use on OpenAI’s website, making it accessible to the masses.

Microsoft and Google are following similar footsteps, with Microsoft making their OpenAI-powered Bing Chat available in a preview, and Google beginning to do the same with Bard. The big tech firms are poised to compete with one another in AI for the foreseeable future, and others will inevitably follow.

That is leading Gartner to predict that by 2026, 100 million workers will have what the firm calls a “robo-colleague,” a synthetic virtual assistant designed to help make users more productive and efficient. Rather than replacing jobs, Karamouzis says there will instead be an evolution where workers use these AI tools to augment their decision-making.

“Will they replace jobs? No, but I think there will be incredible tools that will help recalibrate and redefine how we do work,” Karamouzis says.

The concerns with adopting generative AI in the enterprise

With this pace of innovation and an equal amount of intrigue from organizations and users, the vendor landscape has shifted to focus on AI and finding ways to bring the technology to customers.

Now, the question becomes how enterprises and IT leaders put the technology to good use. However, Karamouzis says that may be easier said than done, predicting that less over the next two years, less than 15% of enterprises are doing to derive meaningful value from it generative AI.

One of those roadblocks may be the ethical, legal and regulatory concerns over the use of these advanced AI models, says Svetlana Sicular, a vice president analyst at Gartner focused on data and AI.

Many regulations exist that govern the use of data, but Sicular anticipates much more red tape around the use of data in AI models. In fact, many such regulations are already in draft form, and regulators everywhere are well aware of these new AI capabilities.

Around ethics, there are serious concerns around plagiarism and essentially, if ChatGPT should be an author or not. Whether or not organizations should disclose that content was created by generative AI is a big question.

Other concerns around data security may be less obvious, but represent an area where enterprise IT leaders may want to approach with great caution, Sicular says.

“If you go directly to the link to ChatGPT, your data is their data,” the AI researcher and analyst says. “Their training their model on your data, and people don’t realize it.”

With enterprises intrigued about the possible use cases of these advanced AI tools, they should think carefully about creating guidelines. However, what keeps Sicular thinking positively about the adoption of generative AI is that these concerns are being raised at the forefront of its emergence rather than after adoption is already widespread.

Sicular compares this to the emergence of social media, for which IT leaders and enterprises were not totally prepared.

“The alarms for AI were raised earlier in the cycle than for social media, which gives me hope that we will do the right thing,” Sicular says.

Enterprise adoption of generative AI and ChatGPT

As with any other emerging or trending technology, enterprises should remain open to the possible use cases and do their due diligence on how best to deploy generative AI models and intelligent virtual assistants.

Sicular suggests simply letting technology leaders explore its capabilities and use cases, but doing so safely and securely.

Coding has emerged as a popular early use case of generative AI, with programmers using these tools to generate code that is then quality checked by human experts. The human control of these programs, Sicular says, is key.

Microsoft has adopted the term “copilot” for its OpenAI integrations across its products, and that is a framing that bodes well for the industry, Sicular says.

“I like the name copilot. It reflects that you’re in charge,” Sicular says. “You’re asking someone trusted to help your or take on some of your tasks and give you the result of those tasks.”

Sicular also recommends that organizations have an open discussion about the possible use cases, encouraging users to share their experiences and allow use cases to grow organically based on that success.

“That’s where use cases will surface,” Sicular says. “It will take time for the enterprise to find those use cases, but if you allow people to experiment, you will see some interesting ideas that will make enterprises competitive or help them do certain things in a new way.”

The post IT Leaders Should Prepare for Generative AI in the Enterprise appeared first on My TechDecisions.

“D&A is in the business of driving stakeholder value,” said Donna Medeiros, senior director analyst, at Gartner in a statement. “The most successful CDAOs are outperforming their peers by projecting an executive presence and building an agile and strategic D&A function that shapes data-driven business performance and operational excellence.”

Successful CDAOs Traits 

The survey found that D&A leaders who rated themselves as “effective” or “very effective” across 17 different executive leadership traits correlated with those reporting high organizational and team performance. For example, 43% of top-performing D&A leaders reported effectiveness in committing time to their own professional development, compared with 19% of low performers.

“Successful CDAOs must be elite leaders,” said Alan Duncan, distinguished VP analyst, Gartner, in a statement. “Top-performing CDAOs invest in their success by developing skills to thrive in ambiguous circumstances, articulate compelling value stories and identify D&A products and services that can drive business impact.”

CDAOs New Demands

The survey found that CDAOs are tasked with a broad range of responsibilities, including defining and implementing D&A strategy (60%), oversight of D&A strategy (59%), creating and implementing D&A governance (55%) and managing data-driven culture change (54%).

Furthermore, many D&A functions are receiving increased investment, including data management (65%), data governance (63%) and advanced analytics (60%). The mean reported D&A budget is $5.41 million, and 44% of D&A teams increased in size in the last year.

“The demands being placed upon D&A, as well as increased investment, reflect a growing confidence in CDAOs’ abilities and recognition of the data office as an indispensable business function,” said Medeiros. “However, this leads to more work as pressure grows for D&A to achieve tangible business results.”

Roadblocks to the Success of D&A Initiatives 

Given the scope and complexity of demands being placed on D&A teams, the lack of available talent has quickly become a top impediment to success, as reported by 39% of respondents. The top six roadblocks reported in the survey are all human-related challenges, as shown in figure below.

To build an effective D&A team, CDAOs must have a robust talent management strategy that goes beyond hiring ready-made talent, says Gartner. This should include education, training and coaching for data-driven culture and data literacy, both within the core D&A team and the broader business and technology communities.

D&A Performance & Business Strategy Alignment

The survey found that 78% of respondents rank corporate or organizational strategy and vision as one of the top three inputs to the D&A strategy. Additionally, 68% are prioritizing D&A initiatives based on alignment to strategic goals.

“CDAOs who prioritize strategy over tactics are the most successful,” said Duncan. “Because the CDAO serves multiple stakeholders across the business, they must align with organizational strategic priorities and focus on selling the D&A vision to the CEO, CIO and CFO as key influencers.”

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