Getting to Know Data Science and Artificial Intelligence

Data science and artificial intelligence are all the buzz. But these terms are not interchangeable. What are they and how should they be used by organizations for maximum strategic value?

What is Data Science? Data science is a continuous process of collecting massive amounts of data to observe, form and test models (or assumptions). This mix of programs, statistics, domain expertise, calculations and visualizations helps find hidden patterns and trends in your enterprise data to support informed and predictive decision making.

What is Artificial Intelligence? AI, a subset of data science, is a collection of programs and algorithms that uses machine learning and deep learning to simulate human intelligence. AI algorithms learn, reason and self-correct to perform autonomous actions and solve problems as they continue to capture more data. AI can translate, understand speech and make decisions self-sufficiently—helping you automate repetitive tasks or strategically innovate products and services.

Data Science

Goal: Curate data to find hidden patterns and trends

Powered by: Statistical techniques and data analytics that finds data patterns to make informed decisions

Used for:
  • Identifying patterns and trends
  • Providing statistical insights
  • Quick calculations or mathematical processing
  • Providing predictive analytics

Artificial Intelligence

Goal: Leverage data to simulate human intelligence

Powered by: Machine learning and deep learning to impose intelligence (using data) to respond like humans

Used for:
  • Automating repetitive tasks
  • Precision
  • Logical, non-emotional decision making
  • Performing risk analysis

Effectively using a combination of data science and AI enables personalized experiences, better operations, and confident decision making.

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Four Keys to Becoming a Data-Driven Organization

Although data is readily available to any organization, only a handful of industry leaders have mastered the craft of managing it. The fact is collecting data is easy. Accessing it, making sense of it, securing it and putting it to good use are far more difficult.

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Data Fuels AI & AI Enabled Technologies

Artificial intelligence has gone from buzzword to transformational technology, but most organizations will never realize its full potential. Why? Because only 10% of organizations are confident in their data.

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In Data We Trust But Do We

While 78% of companies in North America understand the value of their data, only 43% of those surveyed agreed that data plays a pivotal role in the decision-making processes in the company. How do you get senior leaders to see the value in data and trust it?

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Information is Power: The Benefits of Data Science & AI

Some 79% of executives say they understand the value of data, but only one in 10 use it to transform their organization. Almost 50% of executives believe if they don’t implement AI they will lose customers or dent the bottom line, yet the focus on making sure they have accessible, unbiased data to fuel AI and AI-enabled technologies seems to get pushed aside. So how do you realize the benefits of these powerful technologies?

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See how an elite group of executives in 8 industries stand out when it comes to harnessing the power of AI

“Function over Form’” is the important notion to consider when it comes to successfully applying Data science and AI in your organization. For data to become one of your most valuable assets, you must identify your organization’s strategic priorities and then determine how data, analytics and artificial intelligence helps you reach your specific goals, like:

  • Attracting and retaining loyal customers
  • Keeping your employees happy and engaged
  • Differentiating your products and services
  • Optimizing your operations
  • Identifying trends that enable confident decision-making

Leading your organization with a data-first strategy ensures you drive organizational value—no matter your goal. As you prepare to leverage data and artificial intelligence, consider this advice:

  • Get ahead of change and be ready for it to accelerate. Organizations must have the skilled talent, processes, and performance metrics in place to ensure effective implementation of the technology, increase agility and resilience, and drive further innovation
  • Don’t expect it to be easy. Leveraging data science and integrating AI and AI-enabled technologies across your organization demands a clear plan for tools, data governance, skills and leadership—and a thorough sense of what barriers to expect along the way.
  • Understand that transformation means more than technology and starts at the top. AI presents one of the great leadership challenges of our time. Transformation starts at the top; senior leaders must manage change in every phase of implementation, leverage partnerships, and apply function- and industry-specific best practices.
  • Commit to ethics and transparency at every turn. Organizations must implement data governance and AI ethics programs to review all AI projects and articulate both desired results and possible unintended outcomes, ensure AI traceability and transparency and regularly perform audits to ensure that outcomes aligned to your goals as AI technologies continue to learn.
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