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Some argue gen AIs emergence has rendered digital transformation pass. Others suggest everything should be called business transformation or just transformation for short. AI transformation is the term for them. What terminology should you use?
The Critical Distinction Your Organization Can't Afford to Miss As an independent AI and BusinessIntelligence consultant who has worked with organizations across healthcare, hospitality, agriculture, and marketing, I've observed a clear pattern. What Is Data Literacy, and Why Isn't It Enough?
Perhaps we got digital transformation wrong this whole time. Instead of focusing on the transformation part, we did a lot less transforming and a lot more digitalization. Instead of seeing digital as a new paradigm for our business, we over-indexed on digitizing legacy models and processes and modernizing our existing organization.
Agentic AI will integrate smoothly with ERP, CRM, and businessintelligence systems to automate workflows, manage data analysis, and generate valuable reports, says Rodrigo Madanes, global innovation AI officer at EY, a consulting and tax services provider.
For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Together, these capabilities enable terminal operators to enhance efficiency and competitiveness in an industry that is increasingly datadriven.
In todays economy, as the saying goes, data is the new gold a valuable asset from a financial standpoint. A similar transformation has occurred with data. More than 20 years ago, data within organizations was like scattered rocks on early Earth.
From nimble start-ups to global powerhouses, businesses are hailing AI as the next frontier of digital transformation. The Nutanix State of Enterprise AI Report highlights AI adoption, challenges, and the future of this transformative technology. Nutanix commissioned U.K.
The 2024 Enterprise AI Readiness Radar report from Infosys , a digital services and consulting firm, found that only 2% of companies were fully prepared to implement AI at scale and that, despite the hype , AI is three to five years away from becoming a reality for most firms. How confident are we in our data?
As a consequence, these businesses experience increased operational costs and find it difficult to scale or integrate modern technologies. This allows for a more informed and precise approach to application development, ensuring that modernised applications are robust and aligned with business needs.
AI requires us to build an entirely new computing stack to build AI factories, accelerated computing at data center scale, Rev Lebaredian, vice president of omniverse and simulation technology at Nvidia, said at a press conference Monday. They can predict the next token in modes like letters or words.
Noting that companies pursued bold experiments in 2024 driven by generative AI and other emerging technologies, the research and advisory firm predicts a pivot to realizing value. Forrester predicts a reset is looming despite the enthusiasm for AI-driven transformations.
Forrester reports that 30% of IT leaders struggle with high or critical debt, while 49% more face moderate levels. Even in the case of moderate to low risk, technical debt impacts can change quickly as business needs evolve. Using the companys data in LLMs, AI agents, or other generative AI models creates more risk.
As such, the data on labor, occupancy, and engagement is extremely meaningful. Here, CIO Patrick Piccininno provides a roadmap of his journey from data with no integration to meaningful dashboards, insights, and a data literate culture. You ’re building an enterprise data platform for the first time in Sevita’s history.
In a survey of 451 senior technology executives conducted by Gartner in mid-2024, a striking 57% of CIOs reported being tasked with leading AI strategies. While some of the surveyed employees in the US, the UK, Australia, India, and China reported saving an average of 3.6
According to AI at Wartons report on navigating gen AIs early years, 72% of enterprises predict gen AI budget growth over the next 12 months but slower increases over the next two to five years. CIOs should speak to sales leaders to identify areas where sales metrics are underperforming and where gen AI-driven improvements can drive revenue.
Data is the foundation of innovation, agility and competitive advantage in todays digital economy. As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Data quality is no longer a back-office concern.
UIPaths 2025 Agentic AI Report surveyed US IT execs from companies with $1 billion or more in revenue and found that 93% are highly interested in agentic AI for their business. The study found better oversight of business workflows to be the top perceived benefit of it. Another area is democratizing data analysis and reporting.
Jeff Schumacher, CEO of artificial intelligence (AI) software company NAX Group, told the World Economic Forum : “To truly realize the promise of AI, businesses must not only adopt it, but also operationalize it.” Decision-making based on intuition, common sense, and knowledge is very good and should never be lost.
They are using the considerable power of this fast-evolving technology to tackle the common challenges of cloud modernization, particularly in projects that involve the migration and modernization of legacy applications a key enabler of digital and business transformation. The result is a more cybersecure enterprise.
One of the world’s largest risk advisors and insurance brokers launched a digital transformation five years ago to better enable its clients to navigate the political, social, and economic waves rising in the digital information age.
That was my first push into technology, and utilizing it to streamline processes, data, the way people worked, and have it fully integrated into a full stack solution, she says. My team across the whole business supports the run technology for all business units. No two days are the same, she says.
s two major airports has developed a real-time intelligence platform dubbed Queue Hub that harnesses analytics, AI, IoT, and cloud to make terminal operations more efficient and profitable. Overall, Queue Hub has reduced wait times by an estimated 15%, MWAA reports, and Dulles has one of the shortest security wait times — on average 10.5
One of the world’s largest risk advisors and insurance brokers launched a digital transformation five years ago to better enable its clients to navigate the political, social, and economic waves rising in the digital information age.
AI at Wharton reports enterprises increased their gen AI investments in 2024 by 2.3 Experienced CIOs know there is never a blank check for transformation and innovation investments, and they expect more pressure in 2025 to deliver business value from gen AI investments.
Logistics giant GXO, for instance, has signed a multi-year agreement with Agility Robotics, and has deployed Agilitys Digit humanoid robot in a Spanx warehouse facility. Currently, Digit robots assist with repetitive tasks, such as moving totes and placing them onto conveyors.
As someone deeply involved in shaping data strategy, governance and analytics for organizations, Im constantly working on everything from defining data vision to building high-performing data teams. My work centers around enabling businesses to leverage data for better decision-making and driving impactful change.
As a consequence, these businesses experience increased operational costs and find it difficult to scale or integrate modern technologies. This allows for a more informed and precise approach to application development, ensuring that modernised applications are robust and aligned with business needs.
A network of hardware and software is used for this, known as Supervisory Control and Data Acquisition (SCADA), usually connected to a human machine interface (HMI). In contrast, classicIT revolves around systems that manage data and applications. One requirement could be a specific protocol for data access, for example.
A sharp rise in enterprise investments in generative AI is poised to reshape business operations, with 68% of companies planning to invest between $50 million and $250 million over the next year, according to KPMGs latest AI Quarterly Pulse Survey. Profitability remains a close second, surging from 35% in early 2024 to 73% by years end.
Analysts predict the incoming phase of enterprise AI will herald agentic systems that require minimal human intervention, with 75% of CIOs increasing their AI budgets during this year alone, according to a recent report from Gartner. AI makes edge computing more relevant to CIOs because it helps us reduce delays in processing data.
There are also pure-play agentic AI platform providers such as CrewAI and intelligent automation providers like UiPath. In a report released in early January, Accenture predicts that AI agents will replace people as the primary users of most enterprise systems by 2030. And thats just the beginning.
In especially high demand are IT pros with software development, data science and machine learning skills. Government agencies and nonprofits also seek IT talent for environmental data analysis and policy development.
The new packages unveiled at its Sapphire customer event in Orlando this week are for the cloud-based SAP Business Suite announced in February. (It Each of the new packages includes Cloud ERP, business applications, SAP BusinessData Cloud (BDC), SAP Business AI, powered by the SAP Business Technology Platform (BTP).
And, of course, many early projects will fail to offer any actual business value, making them a waste of time and resources. According to a September IDC survey , 70% of CIOs reported a 90% failure rate for their custom-built AI app projects, and two-thirds reported a 90% failure rate with vendor-led AI proof-of-concepts.
Several outsourcing relationships are showing early signs of stress, particularly in security, app modernization, and high-stakes digital programs. Providers are reporting higher margins, but CIOs are seeing increased bills — driven by bundled AI surcharges. Traditional T&M contracts are fast disappearing.
With a cloud-powered digital core in place, organizations can unlock advanced intelligence, industry-specific cloud innovations, enterprise efficiency and agility, and integrate new technologies, such as AI-enabled decision-making, he says. Reinvention-ready companies are positioned to succeed in the long term, Tay observes.
Additionally, GenAI can generate insights from energy consumption data, factoring in elements such as weather and economic activity to boost operational efficiency. With over 1,000 data points to manage, and 74% of organisations still using spreadsheets, technology becomes essential for efficient, compliant reporting and insightful analytics.
With data central to every aspect of business, the chief data officer has become a highly strategic executive. Todays CDO is focused on helping the organization leverage data as a business asset to drive outcomes. Even when executives see the value of data, they often overlook governance.
The growing importance of ESG and the CIO’s role As business models become more technology-driven, the CIO must assume a leadership role, actively shaping how technologies like AI, genAI and blockchain contribute to meeting ESG targets.
One large bank that implemented an AI fraud detection agent reported a significant drop in fraud losses in the first year of use, thanks to the AI’s ability to catch fraudulent transactions that slipped past older controls. Predictive analytics and AI-driven automation are now key to modern insurance operations.
Challenge: Consumers want to shop on their own terms Recent research shows that 77% of consumers today buy through a mix of digital and physical shopping, while just 17% buy only online or only in physical stores (IDC Retail Insights: Consumer Sentiment Survey, 2024 — Findings and Implications, July 2024).
At AWS re:Invent 2024, we introduced a no code zero-ETL integration between Amazon DynamoDB and Amazon SageMaker Lakehouse , simplifying how organizations handle data analytics and AI workflows. By using Apache Iceberg format, the integration provides reliable performance with ACID transaction support and efficient large-scale data handling.
Time and again, we hear from digital and IT leaders that this is the biggest missing piece. Many of our clients target an 80/20 split: 80% of the work is driven by perpetually funded product teams. These teams manage their backlogs and sequence work based on business needs across run, grow and transform domains.
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