Fanning the flames of innovation: Three ways to strengthen the AI and data bond

Artificial intelligence (AI) has been making waves, with the emergence of generative AI, in particular ChatGPT, stealing the spotlight. We’ve gone from building AI to building with AI.

Over the years, cloud computing has played a vital role in the development and deployment of AI. With AI becoming increasingly accessible, more employees are recognizing its value as a tool to enhance and support their work. The advent of generative AI also has revolutionized the way we interact with technology, opening up innovative avenues for engagement and collaboration.

It's no longer just the big players with deep pockets that can use AI; companies of all sizes are benefitting from it. From automating processes and elevating customer experiences to co-creating content, AI is reshaping the way we work, interact and create.

And what’s more exciting is data’s role in all of this. AI and data are the ultimate power couple, with data supplying what’s needed to power AI capabilities and AI, in turn, relying on data to offer true value to the organization. Together they can solve complex problems and create new opportunities.

Data is the accelerator to AI usage while the cloud provides the infrastructure and platform that serves as the accelerator for AI adoption. Organizations’ cloud investment unlocks exciting new opportunities with AI by facilitating easy collaboration and access to AI models, data and services on demand. AI can be used to automate tasks, improve decision-making and create new products and services.

Wherever your organization stands in its cloud journey, embracing the value of your data and the latest AI advancements presents a significant opportunity to address business challenges and tackle your unique use cases. The fusion of AI and data leads to extraordinary business outcomes that leave a lasting impact.

But, as with any successful relationship, it takes effort to keep the spark alive. Here are three ways to help AI and data build a long, successful relationship that delivers real business value.

#1—Get better acquainted

Dating apps have transformed modern love and revolutionized the way we connect with others; similarly, cloud providers and their vast marketplaces have ushered in a new era of possibilities. One of the key benefits of cloud providers is their vast collection of prebuilt AI models and solutions tailored to specific industries and line-of-business use cases. This dynamic ecosystem offers an extensive array of models, cognitive services and complementary cloud services for accelerating AI adoption and the value of the AI-data connection. 

Whether you are a budding startup or an established corporation, cloud providers ensure that AI is within reach for all. The ease of these capabilities transcends organizational boundaries and is available at any stage of AI adoption. This democratization of AI means that organizations of all sizes can harness its potential, empowering employees and teams throughout the company to leverage the benefits of AI.

Here are just a few examples of cloud solutions that bring data and AI together:

• Microsoft AI Builder, part of Microsoft Power Platform, provides a no-code experience to bring the power of AI to your organization, without the need for coding or data science skills.
• Azure Cognitive Services enables teams to add cognitive capabilities to apps with APIs and AI services.
• AWS AI Services, including pre-trained services like Amazon Comprehend, Forecast and Rekognition, employ machine learning to automate image recognition and video analysis, and augment human review with AI and industry-specific tasks, like extracting information from unstructured medical notes, clinical trial reports and radiology reports.
• Google Vertex AI offers a unified data and AI platform and tooling for pre-trained and custom models to rapidly prototype for building generative AI apps responsibly to managed Machine Learning tools for any use case.
• Generative AI App Builder enables developers to build new generative AI-powered search and conversational experiences.
• OpenAI provides an array of resources, including research, APIs, models, plugins and developer tools and libraries.
• Amazon Bedrock and Amazon SageMaker offer access to models from AI21 Labs, Anthropic, Stability AI and Amazon via APIs to build and scale generative AI-based applications.

Text analytics, speech, vision and machine language translation AI models can be integrated into small and enterprise systems. Use these AI models to optimize data entry and capture and analyze unstructured data like notes and documents – all without machine learning expertise. Deploy more sophisticated, industry-specific AI models for targeted, timely access to insights, recommendations, predictions, diagnoses and more through intelligent application interfaces such as laptops, handhelds and mobile kiosks. 

#2—Nurture the relationship 

To fully reap the benefits of this dynamic duo, it's important to understand how AI and data can work together for your organization. With generative AI and technology advancing rapidly, it's crucial to know how to seamlessly integrate AI into your organization and its unique pains, needs and priorities. Here are a few key steps to take:

• Identify business challenges: Specifically, look at areas where AI can create the most value for your existing business processes, applications and programs. These may be areas where manual processes can be automated, decision-making can be improved, or new products and services can be developed.
• Prioritize and create high-impact use cases: Figure out what you’re trying to use AI to solve. Clear, focused AI use cases lay the foundation for AI implementation and drive business value and innovation.
• Assess in-house talent and source external expertise: You don’t need a data science team to get started with AI. Most companies find there’s real value in leaning on experienced partners to help them on their journey and begin taking advantage of pre-built AI models.
• Create a cross-functional team: Even the happiest pairs need people to back them up. Assemble a team with diverse areas of expertise – including data, IT, business and legal – to help with the implementation, testing and adoption.

#3—Foster a future

Every relationship requires work for long-term success. For AI and data, that means building on cloud infrastructure, strategizing your data and AI approach and including an intelligence layer. Here are some essential components that contribute to a successful partnership:

• A business-aligned AI strategy: Extend your organization’s data, technology and business strategy to incorporate AI strategy. For instance, align it with your overall business strategy to ensure that AI initiatives support the organization's objectives.
• Security measures: Protect data privacy and confidentiality and ensure your practices comply with industry and regulatory standards like HIPAA, PCI and GDPR.
• Data, analytics, machine learning and AI services: Provide access to machine learning and AI services, including pre-built algorithms, APIs and tools, in your well-architected cloud foundation to build and deploy AI models quickly and easily.
• Intelligent applications, visualization tools and interfaces: Gain access to AI-generated insights and predictions with visualization capabilities so you can make informed decisions. 

Make sparks fly and productivity soar

The union of AI and data is much stronger if you take intentional steps. With the help of prebuilt solutions and strategic planning, you can nurture the relationship and establish a solid foundation. Connect these powerful technologies so they can deliver tremendous value to your organization. While beach strolls at sunset are optional, increased productivity is a given when these two come together.

Explore how Unisys can help you unlock limitless possibilities of AI and data. 

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