Artificial intelligence (AI) is rapidly changing the world. From self-driving cars to facial recognition software, AI is already having a major impact on our lives.
Take the best parts of our state-of-the-art tools and add your own innovations. Whether you need natural language processing, computer vision, or speech recognition, we have the right AI solution for you.
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Step 1: Define your strategic goals and vision
Plan how AI can enhance, accelerate, or augment your existing business objectives and capabilities. Align your AI projects with your key differentiators, initiatives, or long-term goals.
Step 2: Assess your current AI maturity
Evaluate and identify the gaps and opportunities in your data infrastructure, talent, culture, and governance. Develop a roadmap to address these challenges and leverage your strengths.
Step 3: Implement and iterate
Deploy your AI projects using best practices and frameworks for data science, model development, testing, and deployment. Use tools and platforms that enable scalability, flexibility, and integration with your existing systems and workflows.
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Industries
Grow faster with AI-powered deep industry expertise
Adapt. Streamline. Thrive. Leverage our industry and digital expertise with AI to make your business more agile—and more competitive.
Automotive
Leveraging AI to enhance safety, efficiency and personalization of vehicles and mobility services
Banking
Using AI to improve customer service, risk management and compliance across various banking functions and channels
Capital Markets
Applying AI to optimize trading, investment and operations by using advanced analytics, automation and natural language processing
Communications, Media & Technology
Harnessing AI to create engaging and intelligent content and services that cater to diverse customer needs and preferences
Consumer Goods
Empowering AI to drive innovation, loyalty and growth by enabling personalized marketing, product development and supply chain management
Education
Enabling AI to support personalized and adaptive learning by providing customized content, feedback and assessment for learners and educators
Healthcare
Deploying AI to improve diagnosis, treatment and care delivery by facilitating data integration, clinical decision support and patient engagement
Information Services
Generating AI to unlock new insights and value from data by offering data-driven products, solutions and platforms for various industries and domains
Insurance
Adopting AI to enhance customer experience, underwriting and claims by leveraging data analytics, automation and chatbots
Life Sciences
Advancing AI to accelerate drug discovery, development and delivery by streamlining research, clinical trials and regulatory processes
Manufacturing
Integrating AI to boost productivity, quality and sustainability by enabling smart manufacturing, predictive maintenance and waste reduction
Natural Resources
Leverage AI technologies, analytics, automation and process re-engineering to enhance exploration, production and sustainability
Oil & Gas
Utilizing AI to optimize exploration, production and distribution by applying data analytics, automation and computer vision
Retail
Transforming retail with AI-powered customer insights, recommendations and operations by using data mining, machine learning and natural language processing
Software Platforms
Deliver faster time to market and cost efficiencies with AI-powered software development and sustenance services including gamification
Transportation & Logistics
Improving transportation and logistics with AI-enabled routing, tracking and forecasting by using optimization, computer vision and deep learning
Travel & Hospitality
Reinventing travel and hospitality with AI-driven personalization, automation and optimization by using natural language processing, recommender systems and sentiment analysis
Utilities
Driving innovation, growth and greater efficiency with AI-enabled smart grids, demand response and customer engagement by using data analytics, automation and machine learning
Our blog showcases AI insights, tutorials, projects, tips and news. Whether you are a beginner or an expert, you will find something useful and interesting here. Join us as we explore the fascinating world of artificial intelligence and its applications.
Meta has published a deep dive into the company’s social media algorithms in a bid to demystify how content is recommended for Instagram and Facebook users. In a blog post published on Thursday, Meta’s President of Global Affairs Nick Clegg said that the info dump on the AI systems behind its algorithms is part of the company’s “wider ethos of openness, transparency, and accountability,” and outlined what Facebook and Instagram users can do to better control what content they see on the platforms. “With rapid advances taking place with powerful technologies like generative AI, it’s understandable that people are both excited by the possibilities and concerned about the risks,” Clegg said in the blog. “We believe that the best way to respond to those concerns is with openness.”
The buzz around artificial intelligence has investors snapping up shares of startups on alternative venues, looking to find the next wave of technology giants before they even go public. AI and machine learning have remained the most in-demand sectors every month this year, accounting for 25% to 30% of investor interest, according to EquityZen Securities Inc., a marketplace for privately held shares. On Rainmaker Securities, a platform that facilitates secondary stock transactions for private businesses, investors are paying up for shares of companies like OpenAI and Anthropic, startups that are seen as leading the pack in AI.
The league has partnered with Uplift Labs, a biomechanics company that says it can document a prospect’s specific movement patterns using just two iPhone cameras. The setup was available for use in evaluating prospects who agree to participate at the MLB draft combine last week in Arizona. Uplift says it uses artificial intelligence to translate the images captured by the phone cameras into metrics that can quantify elements of player movement. It believes the data it generates can detect player’s flaws, forecast their potential and, possibly, flag their potential for injury.
The Europe Union is introducing “crash test” systems for artificial intelligence to ensure new innovations are safe before they hit the market. The trade bloc launched four permanent testing and experimental facilities across Europe on Tuesday, having injected €220 million ($240 million) into the project. The centers, which are virtual and physical, will from next year give technology providers a space to test AI and robotics in real-life settings within manufacturing, health care, agriculture and food, and cities.
FAQs
AI in the Enterprise
Opportunities, challenges, and best practices for adopting AI in the enterprise: Only the most frequently answered questions
What is AI in the enterprise?
AI in the enterprise is the application of artificial intelligence technologies, such as machine learning, natural language processing, computer vision, and automation, to enhance, accelerate, or augment existing business processes and outcomes. AI in the enterprise can help save money, boost efficiency, generate insights, and create new markets.
Why is AI important in the enterprise?
AI is important in the enterprise for developing a successful business strategy that can benefit from powerful and rapidly evolving technologies. AI in the enterprise can help improve operational scalability, agility, innovation, and resilience. AI in the enterprise can also help address complex and urgent problems, such as the COVID-19 pandemic.
What are some use cases for AI in enterprises?
Customer service: use of AI to enhance customer interactions, provide personalized recommendations, automate responses, and increase satisfaction.
Sales: use of AI to optimize pricing, forecasting, lead generation, and cross-selling.
Cybersecurity: use of AI to detect and prevent potential attacks, fraud, and breaches.
Supply chain: use of AI to optimize inventory, logistics, demand planning, and quality control.
Human resources: use of AI to streamline recruitment, training, performance management, and retention.
Product development: use of AI to accelerate innovation, design, testing, and launch of new products or services.
What are some challenges for AI in enterprises?
Data quality and availability: ensuring that the data used for AI is accurate, complete, consistent, and accessible.
Data governance and security: ensuring that the data used for AI is compliant with ethical and regulatory standards, and protected from unauthorized access or misuse.
Skills and culture: ensuring that the organization has the right talent, mindset, and collaboration to develop and deploy AI solutions.
Scalability and performance: ensuring that the AI solutions can handle increasing volumes and complexity of data and requests without compromising quality or speed.
Trust and transparency: ensuring that the AI solutions are explainable, reliable, fair, and accountable.
What are some best practices for AI in enterprises?
Define your business objectives and use cases for how AI can enhance, accelerate or augment your existing business processes and outcomes.
Assemble an AI governance board to set the strategic direction, ethical framework, goals and funding of your AI program.
Gather relevant data and build a skillful team to support your AI projects.
Train and validate your AI model using data, code and frameworks that meet your performance criteria and business objectives.
Deploy your AI model to a pre-production or production environment using online or batch deployment options.
Monitor, manage and improve your AI model using metrics, dashboards and feedback loops to track its performance, accuracy, reliability and impact.
50%
50% of surveyed leaders cite managing AI-related risk, lack of executive commitment, and lack of maintenance and post-launch support as top challenges to scaling AI across departments or businesses
3x
The number of enterprises implementing AI tripled in the past year, but they also struggle with acute talent shortages, as only 7% of them have AI experts on staff
10x
91% of the ten most successful companies are making investments in AI, and companies that have already adopted AI will be ten times more effective than those that have not by 2025
94%
94% of respondents in a global survey say AI is critical to success over the next five years, and 79% of them have fully deployed three or more types of AI technologies
AI + You
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