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Welcome to the Future of Business: Harnessing AI and Machine Learning Effectively

Artificial intelligence (AI) and machine learning (ML) have emerged as essential drivers of innovation, efficiency, and competitive advantage in the B2B IT landscape. As technology continues to reshape industries, forward-thinking businesses are leveraging AI and ML to transform operations, enhance decision-making, and unlock new opportunities for growth.

The Potential of AI is Staggering

By 2030, AI is anticipated to contribute a remarkable $15.7 trillion to the global economy, highlighting its transformative potential across various industries. The potential of AI is staggering. However, the path to successful AI implementation is complex. With 87% of AI/ML projects failing to reach production due to poor data quality and 42% of data leaders citing it as their primary hurdle, the need for expert guidance and robust strategies has never been more critical.

Navigating the AI landscape requires a combination of deep industry knowledge, cutting-edge expertise, and a proven approach. Whether you’re looking to enhance customer service, strengthen cybersecurity, or drive operational efficiencies, the right AI and ML solutions can help you not only succeed but deliver tangible business value.

%

AI/ML Projects Fail Due to Poor Data Quality

%

Of Leaders Say Poor Data Quality Biggest Hurdle

Explore Our Resources For a Deep Dive Into AI and ML

How to Create an AI/ML Roadmap

In this in-depth white paper, you’ll learn how to create an AI/ML roadmap that sets your organization up for long-term success with this transformative technology.

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Is Your Data Ready for AI/ML?

In this white paper, we’ll help you understand the common mistakes that happen when implementing AI/ML solutions, the challenges with data quality and preparation, and the foundation for AI/ML success.

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AI & ML: The Future Analyzed

AI & ML share traits but are different from each other. In this white paper, dive into the history, fundamentals and how they impact corporate performance.

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Tips for Machine Learning Model Selection

As a ‘self-teaching’ system, ML evolves based on the information that feeds it. Learn how ML models work and how to choose the right one to suit your needs.

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Benefits and Use Cases of AI/ML

Increased Innovation and Speed-to-market →

Better Customer Experience →

Accelerated Marketing Campaigns and Sales →

Improving Revenue and Growth →

Lowering Overall Business Costs →

Predicts Customer Behavior →

Enhance Production Values →

Improve Corporate Security →

Data Quality is Key to AI/ML Success

The success of your AI/ML initiatives hinges on one critical factor: data quality. High-quality data not only streamlines AI operations—leading to efficiency gains and reduced operational costs—but also plays a vital role in risk mitigation, ensuring reliable and safe AI responses.

As businesses strive to optimize resource utilization and safeguard sensitive information, understanding the impact of data quality on AI/ML adoption has never been more essential. The financial implications are staggering, as poor data quality costs businesses an average of $12.9 million annually.

Organizations that embrace AI are reaping significant benefits, with 4.8x greater labor productivity growth compared to average, AI adopters are 1.5 times more likely to experience top-quartile revenue growth in their industries, and 63% of businesses utilizing AI report direct revenue increases.

%

Of Businesses Using AI Report Revenue Increases

AI/ML Adoption Barriers

Unclear Objectives →

Lack of Skilled Talent →

Neglecting Change Management →

Limited Infrastructure Scalability →

Inadequate Model Evaluation and Monitoring →

Unrealistic Expectations →

Neglecting Ethical Considerations →

Data Quality and Governance Challenges →

Datavail’s AI/ML Consulting and Implementation Solutions

Datavail’s Data Management and Analytics practice has 100s of experts dedicated to delivering a wide range of data services to take you through building your AI/ML data foundation, creating a roadmap, and building your proof of value.

Assessments

An assessment of your data management and analytics environment with a total cost of ownership (TCO) evaluation. This includes evaluating your entire current platform to determine if your system – from data ingestion, storage through visualization – can support AI and ML capabilities.

Strategic Consulting and Roadmaps

Creating a complete data management and analytics strategic roadmap, to provide a strategy for an advanced analytics platform and capabilities, including AI and ML.

Application Implementation and Integration

Includes architecture, design and deployment of an advanced data analytics system to implement and integrate AI and ML processes and technologies.

AI and ML System Development

Business analysis and data evaluation to assess the viability of a predictive model, prepare it for the appropriate ML algorithm, and manage the model throughout the data science life cycle to ensure accurate predictions.

Managed Services

Providing post-implementation continuous support 24/7/365 for your AI/ML environment.

Datavail’s Approach to AI/ML Solutions

Partnership

Working as an ongoing partner with your team to ensure success of the overall program – this is not a transaction but a journey.

Consultative

We bring expertise in various focus areas and technologies relevant to your solution to lead and own the solution.

Intellectual Property Based

We do not reinvent the wheel with each engagement, we bring proven methodologies, templates, and architectures to jump-start your initiative.

Forward Thinking

We invest in IP, labs, technologies and emerging platforms.

Build and Run

Our approach is to not only build the solution but to build a solution that we can support and leverages our existing support model.

AI/ML Case in Point

Here are some ways Datavail customers are putting AI/ML to use for better business outcomes.

Multi-line Insurance Company

Streamlining and automating actuarial workflows to support business expansion using Python, R, and Apache Spark.

Investment Company

Modernizing existing data warehouse environment from AWS to Azure and implementing Cognitive Search with Open AI to accelerate report creation and improve investment performance.

Full-service Financial Institution

Creating the foundation, infrastructure, and roadmap for a marketing AI/ML solution, building, deploying, and managing predictive customer attribution models with Azure Machine Learning services.

Healthcare Organization

Providing access to real-time critical care data, minimizing human data entry by maximizing automation capabilities, and seamlessly integrating with future data repositories.

Food Manufacturing Company

Optimizing COGS using AI to improve profitability.

AI/ML Solution FAQ

Have further questions about Datavail’s AI/ML solutions? Find your answers on our comprehensive FAQ page. Learn what techniques Datavail uses for preprocessing data, how we can help migrate existing data to the Cloud for AI/ML purposes, how to develop custom AI/ML solutions, and so much more!

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