AI business strategies

Artificial intelligence software is changing how enterprises conduct business. Machine learning supports data-driven decisions, customer service chatbots follow up on leads, robots in manufacturing boost productivity -- the list goes on. Get advice for building and implementing AI business strategies.

June 30, 2022 30 Jun'22
Siemens forges digital twin deal with Nvidia for metaverse

The industrial powerhouse partners with AI hardware/software vendor Nvidia on digital twins, a metaverse technology increasingly used in industrial and manufacturing settings.
June 23, 2022 23 Jun'22
Microsoft reins in AI facial and voice recognition tech

The tech giant plans to rein in some of its AI technologies based on facial and voice recognition to reduce or eliminate bias and discrimination and aim for 'inclusive AI.'
June 13, 2022 13 Jun'22
Alternative data, multimodal AI tech produce new insights

AI fuels the delivery of new sources of investment and corporate information, such as satellite imagery, contact center audio logs, employee sentiment and social media data.
June 01, 2022 01 Jun'22
Analytics, automation and AI will fuel future of business

Organizations that speed their decision intelligence abilities will be those that survive and thrive, while those that don't digitally transform will fail.

Bring yourself up to speed with our introductory content

How hybrid chatbots improve customer experience

Hybrid chatbots combine human intelligence with AI used in standard chatbots to improve customer experience. Learn how industries are using them to engage with customers. Continue Reading
chief digital officer (CDO)

A chief digital officer (CDO) is charged with helping an enterprise use digital information and advanced technologies to create business value. Continue Reading
10 metaverse dangers CIOs and IT leaders should address

The metaverse poses many of the same risks and security pitfalls that the internet does. Here's a look at 10 of those issues and how IT leaders should address them. Continue Reading

Weigh the pros and cons of technologies, products and projects you are considering.

Hybrid AI examples demonstrate its business value

As businesses weigh the potential benefits of implementing AI systems, hybrid AI examples demonstrate the technology's practical value for businesses. Continue Reading
Stochastic processes have various real-world uses

The breadth of stochastic point process applications now includes cellular networks, sensor networks and data science education. Data scientist Vincent Granville explains how. Continue Reading
What is AI governance and why do you need it?

AI governance is a new discipline given the recent expansion of AI. It's different from standard IT governance practices in that it's concerned with the responsible use of AI. Continue Reading

Learn to apply best practices and optimize your operations.

Real-world hyperautomation examples show AI's business value

Hyperautomation examples in the real world help businesses automate as many of their processes as possible and achieve their strategic goals. AI is instrumental in these efforts. Continue Reading
Weighing quantum AI's business potential

Quantum AI has the potential to revolutionize business computing, but logistic complexities create sizeable obstacles for near-term adoption and success. Continue Reading
How AI and automation play a role in ITOps

Tech professionals agree that AI, intelligent automation and cybersecurity play important roles in the enterprise and can revolutionize ITOps when implemented and used correctly. Continue Reading

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

Expanding explainable AI examples key for the industry

Improving AI explainability and interpretability are keys to building consumer trust and furthering the technology's success. Continue Reading
Combating racial bias in AI

By employing a diverse team to work on AI models, using large, diverse training sets, and keeping a sharp eye out, enterprises can root out bias in their AI models. Continue Reading
Tackling the AI bias problem at the origin: Training data

Though data bias may seem like a back-end issue, the enterprise implications of an AI software using biased data can derail model implementation. Continue Reading