Industry executives and experts share their predictions for 2025. Read them in this 17th annual VMblog.com series exclusive. By Tendü
Yoğurtçu, PhD, Chief Technology Officer, Precisely
In 2025, the convergence of data and AI will continue to redefine
the technology and business landscape. As organizations further integrate AI in their respective
workflows, they will streamline traditionally complex business operations
through the use of agentic AI, while also prioritizing
AI models enriched with trustworthy data.
These efforts will hinge on strong data practices, including the implementation
of metadata to drive intelligence, geospatial data and analytics for improved
decision-making and AI governance.
2025 Will Be
the Year of AI Agents
The rise of agentic AI-both autonomous and
augmenting agents designed to interact and make decisions in complex
environments-is expected to reshape workflows. Autonomous agents will operate
independently, making decisions without human intervention, while augmenting
agents will work alongside humans, enhancing their capabilities and
decision-making processes. However, the journey to widespread organizational
trust and adoption will take time. Early adopters will experiment with both
types of agentic AI in low-risk use cases and controlled environments, focusing
on augmenting specific workflows with clear human oversight. Trust will be
built incrementally as organizations see measurable value and understand the
nuances of how agentic AI interacts with decision-making processes.
Additionally, AI will revolutionize user interfaces (UI) and customer
experiences. This transformation will enable more intuitive,
hyper-personalized, and efficient interactions, fundamentally changing how
users engage with technology.
Data Integrity
Will Be the Foundation of AI Success
In 2025, as enterprise AI adoption accelerates, the
focus on powering AI initiatives with high-quality, integrated, and
contextualized data will be critical to success. New research shows 60% of
organizations state that AI is a key influence on their data programs, however
only 12% report that their data is of sufficient quality and accessibility for
AI. Organizations will prioritize investments in data cleansing,
standardization, and enriching their organizational data with 3rd
party data to ensure their AI systems deliver more accurate results leading to
trusted business decisions. High-quality data will no longer be a competitive
advantage but a business imperative. Cost-performance considerations will lead
to a focus on delivering more accurate results with domain-specific and
high-quality data sets, regardless of model sizes.
Metadata Will
Be the Driver for Intelligence
In 2025, metadata will emerge as the linchpin for
unlocking the full potential of data and AI. Active metadata management goes
beyond static descriptions of data by continuously monitoring and enriching
metadata with insights, such as usage patterns, data lineage, and data quality
metrics. Data observability will play a key role in active metadata management,
enabling organizations to set alerts, monitor patterns, and detect deviations
from historical trends. Active metadata is crucial for powering automation and
AI-driven processes, allowing organizations to dynamically optimize data
integration, quality monitoring, governance, and security. This real-time
intelligence will facilitate faster, more accurate decision-making and greater
operational efficiency across distributed data environments.
Location
Intelligence Will Take Center Stage
In 2025, location intelligence will become a
pivotal element in business strategy and operations. By leveraging geospatial
data and advanced analytics, organizations will gain deeper insights into
customer behavior, market trends, and operational efficiencies. Location
intelligence will enable businesses to optimize supply chains, enhance targeted
marketing efforts, and improve customer experiences by providing contextually
relevant information. The integration of location-based data with AI will drive
innovation in areas such as smart cities, logistics, emergency responses, and
hyper-personalized services, making location intelligence a cornerstone of
data-driven decision-making.
AI Regulations
Will Drive Demand for Robust Data and AI Governance
As stringent AI regulations, such as the EU AI Act,
come into effect in early 2025, businesses will increasingly prioritize
embedding robust data integrity strategies centered on governance, quality, and
observability to close this gap. New research shows that 62% of companies cite
data governance as the primary challenge inhibiting AI initiatives, and 71%
report that they will be investing in governance programs. Beyond data
governance, the absence of interpretability and transparency in AI models raises
significant concerns regarding
bias, ethics, accountability, and equity. As organizations aim to
operationalize AI responsibly, robust data and AI governance will play a
pivotal role bridging the gap between regulatory compliance and ethical AI
adoption.
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Tendü
Yoğurtçu, PhD, Chief Technology Officer
Tendü Yoğurtçu, Ph.D., is the Chief
Technology Officer (CTO) at Precisely. In this role, she directs the company's
technology strategy and innovation, leading product research and development
(R&D) programs.Prior to becoming Chief Technology Officer, Tendü served as
General Manager of Big Data for Syncsort, the precursor to Precisely, leading
the global software business for Data Integration, Hadoop, and Cloud. She
previously held several engineering leadership roles at the company, directing
the development of the Integrate family of products.