80% of AI projects fail—not because the technology isn’t ready, but because businesses aren’t. Companies that thrive with AI begin by identifying clear, high-impact problems it can solve, backed by quality data and a strategic vision for success. This article explores the critical elements of AI readiness: defining your business challenges, ensuring your data infrastructure is robust, and leveraging AI to gain a competitive edge. Whether it’s automating repetitive tasks, personalizing customer experiences, or predicting trends, the key to success isn’t adopting AI early—it’s adopting it smartly. Learn how to assess your readiness and prepare for an AI-powered future.

Explore how AI-powered virtual concierges are transforming customer service in industries like hospitality and education. With 80% of customers likely to switch brands after two bad experiences, businesses are turning to AI to meet rising expectations. This article delves into real-world examples of AI concierges offering personalized recommendations, streamlining tasks like bookings and check-ins, and supporting students with career guidance—all while allowing human teams to focus on more complex customer needs.

The global food supply is on the brink of crisis. Facing challenges like an aging workforce, labor shortages, declining crop yields, and climate change amongst others, farming is in dire need of a lifeline. AI and AgTech are emerging as the saviors of agriculture, transforming everything from crop breeding to farm-to-table traceability. These revolutionary technologies promise to enhance sustainability, improve yields, and reduce environmental impact. With the urgency for innovation greater than ever, AI is the essential lifeline the agricultural industry needs to secure a resilient and efficient future.

The global AI market is expected to reach $126 billion by 2025 — however building an in-house AI team can be costly, with an average salary for AI specialists at $150,000 annually. Outsourcing your AI development offers significant advantages, including cost savings, access to expertise, faster implementation, scalability, and the ability to focus on core competencies. Companies can save up to 60% in operational costs and leverage the latest AI technologies without the burden of maintaining a large in-house team, making outsourcing a strategic solution for many businesses.

Chatbots, now omnipresent, face a crisis of accuracy and security highlighted by recent public blunders at Air Canada and Chevrolet, where bots made unintended promises. Air Canada's attempt to deflect blame onto its bot was rejected by authorities, underscoring a harsh reality: companies are indeed responsible for their bots' actions. Despite the prowess of language models like ChatGPT, their inherent nature to occasionally fabricate with confidence poses unique challenges. Drawing lessons from cybersecurity, this article explores four advanced red team testing strategies aimed at reining in bot misstatements and significantly bolstering chatbot security.

In this article, we delve into the evolution of search technologies, tracing the journey from the conventional keyword-based search methods to the cutting-edge advancements in semantic search. We discuss how semantic search leverages sentence embeddings to comprehend and align with the context and intentions behind user queries, thereby elevating the accuracy and relevance of search outcomes. Through the integration of vector databases such as OpenSearch, we illustrate the development of sophisticated semantic search systems designed to navigate the complexities of modern data sets. This approach not only delivers a more refined search experience but also enhances the precision of results by accurately interpreting the intent of user inquiries, representing a notable leap forward in the progression of search technology.

AI chatbots are transforming customer service by providing 24/7 availability and interactions that resemble human conversation. It's anticipated that by 2025, 80% of customer support will utilize Generative AI to improve the customer experience and increase agent efficiency. However, the swift adoption of this promising technology has faced obstacles, particularly miscommunications that have risked brand reputations. To prevent inaccuracies it's essential to adopt thorough AI testing and certification processes. In this article, learn more about why rigorous testing and certification are critical for the successful integration of AI chatbots in customer service.

As 2023 draws to an end, we reflect on a year of remarkable growth and insights in artificial intelligence through the lens of Your AI Injection. This year's episodes have been a treasure trove of knowledge, featuring discussions on AI's role in mental health therapy, the evolution of virtual concierges, AI-assisted memory extension, and more. If you're curious about the future of AI and its practical applications, these episodes offer a compelling and informative journey, illuminating AI's potential to reshape various aspects of our lives. Learn more about our top podcasts of the year in this article:

The Director of Innovation plays a crucial role in a company by staying informed about various technological advancements to maintain the company's competitive edge. In 2024, the key focus is generative AI, a technology prevalent in headlines and discussions across various domains, including everyday settings. Learn more about the relevance of AI in trend analysis, opportunity identification, and strategic planning in this article.

AI has rapidly evolved into a daily necessity by 2023, with GPT-4 marking a significant leap in language models and public awareness. This advancement has spurred transformative changes across various sectors, particularly in creative fields. In this era, companies embracing innovation and risk-taking are leading the new AI age, with generative AI emerging as a pivotal tool reshaping business possibilities.

Recent advancements in AI technology have reshaped everyday life and industries, introducing autonomous functionality in products like Tesla's Autopilot and Roomba, and opening up new frontiers in complex problem-solving. This article explores the rapid progression towards a future where AI is not just a tool, but a collaborative force in driving human progress.

With the rise of AI-powered virtual concierges, businesses have an opportunity to enhance customer service and engagement. These digital assistants can navigate customers through various services and products, and improve the overall customer experience. This article explores five compelling reasons why businesses should embrace virtual concierges to fuel their growth, focusing on improving customer service quality and fostering long-term customer loyalty:

Large Language Models (LLMs) are increasingly popular due to their ability to complete a wide range of tasks. However, assessing their output quality remains a challenge, especially for complex tasks where there is no standard metric. Fine-tuning LLMs on large datasets for specific tasks may be a potential solution to improve their efficacy and accuracy. In this article, we explore the potential ways to assess LLM output quality:

You probably suspect AI can dramatically improve your business, but perhaps you are not sure exactly how -- perhaps you are even worried that a start up or tech company is gunning for your business. Ask yourself two questions: 1. what are the high level business problems that could be transformational if solved and 2. which business problems are feasible to solve with AI to some meaningful degree.

The insurance industry is moving towards a more tech-driven future with the help of natural language processing (NLP). Artificial intelligence could improve productivity and save up to 40% on insurance costs by 2030, according to a 2021 McKinsey report. In this article we address how you can utilize NLP to automate customer service, streamline underwriting, and analyze social media data:

When securing executive buy-in for your potential AI project, there are a number of considerations to keep in mind. It’s necessary to prepare a strong proposal that not only takes account the motivations of your leaders, but also makes a case for your project’s technical feasibility. In this article we dive into five tips to consider when attempting to secure executive buy-in:

The demand for data scientists has never been higher, and 86% of executives claimed that AI would be a “mainstream technology” at their companies in 2021. As Artificial Intelligence becomes more widely adopted in business practices, many companies are beginning to utilize AI Consultancies to optimize customer experience, reduce cost, and more. When starting a new AI initiative, working with an experienced consultant is the way to go. That’s why we curated this list of top 5 reasons you should hire an AI Consultant.

The increasing prevalence of AI education technologies raises questions and concerns about the role of AI in the classroom. We explore AI-powered chatbots, language assessments, grammar assistance, and homework help to show AI’s potential as a tool for increasing access to educational materials and automating tasks for educators, allowing them to focus on complex responsibilities and direct student interactions.

Hearing aids are a crucial assistive technology for the deaf and hard of hearing communities. However, many who would benefit from the use of hearing aids show a reluctance that stems from a lack of confidence in their value. AI is being used to address the concerns of users with the goal of improving accessibility as well as mental health and cognitive outcomes.

AI has the potential to help create a more equitable, efficient, and innovative educational system. Artificial Intelligence is currently reshaping the way students learn in classrooms all around the world. We address six ways that AI can be leveraged to enhance the ever changing educational landscape for students and teachers alike.

Since the first oil well was dug in 1859, we have been extracting carbon from the ground and pumping it into our atmosphere. Similar to the hundreds of thousands of oil wells around the world, what if we had many CCS systems capturing carbon, often in the form of oil, and injecting it back into the ground?

There is strong demand from governments, environmentalists, and citizens alike to keep our oceans clean and preserve the biodiversity and critical services they provide to life on Earth. Many emerging companies and organizations are changing the landscape of ocean conservation by developing innovative AI monitoring techniques and robotic technologies to identify pollution in our oceans and waterways and provide an expedited approach to cleaning it up.

Illegal logging is an environmental and economic loss for tropical regions like the Amazon. Illegal logging is associated with billions of dollars of lost revenue each year in addition to depressed timber prices, yet effective strategies to curb illegal deforestation are hard to find. Harnessing AI serves as a promising innovation for enhancing the accuracy of forest monitoring, with the potential to be adapted to the Amazon basin and other tropical regions.

In recent years, we’ve witnessed the shocking imagery of Australia, the western United States, Europe, and the Amazon rainforest engulfed in flames, the unprecedented intensity, duration, and extent of the fires inflicting irreversible damage on countries, economies, ecosystems, and the atmosphere. Managing and conserving forest resources remains a top priority, but mapping and monitoring global forests are crucial to understanding how to properly manage and protect them, especially in monitoring wildfires and illegal deforestation, as well as knowing which forests to prioritize preserving. Identifying and monitoring forests with strong conservation value and high carbon stock is also a huge leverage point for targeted intervention of Artificial Intelligence.

In this article, we explore some practical uses of AI driven automated text generation. We demonstrate how technologies like GPT-3 can be used to better your business applications by automatically generating training data which can be used to bootstrap your machine learning models. We also illustrate some example uses of language transformations like transforming english into legalese or spoken text into written.

In a world overshadowed by the rapid deterioration of its climate, AI engineers are beginning to apply machine learning technology to issues of environmental justice and crisis. In California, where wildfires have ravaged over 570,000 acres of land and forced 41,000 evacuations already this summer, AI is being used to prevent and monitor forest fires throughout the state.

The application of AI in creative spaces like music and art is not new, but recent years have seen a dramatic expanse in machine learning capabilities in music composition. AI is being used by researchers and startups to compose soundtracks and soundscapes, and to create original songs within the style of specific genres and artists. Just as work by writers regularly appears alongside robot authors in sports, financial, and other news, Human musical artists are increasingly sharing the stage with artificial intelligence.

Within this last year alone, there has been a paradigm shift in model development as research groups are ingesting (nearly) the entire world's worth of information on the internet to train massive deep learning models capable of performing fantastic or frightening feats, depending on your perspective. In this article, we explore an AI compositional technology, known as generative modeling, and demonstrate its ability to simulate human-realistic text.

As an AI Consultant, I get a front row seat to AI and innovation; I repeatedly see when it succeeds, and when it fails. I’ve been building AI and machine learning based systems for over 20 years, in many different companies, cultures, and problem domains. During this time, I’ve noticed a number of patterns that cause the deployment of AI systems and AI powered features to fail.

In 1912, the RMS Titanic hit an iceberg in the North Atlantic Ocean about 400 miles south of Newfoundland, Canada and sank. Unfortunately, there were not enough lifeboats onboard to accommodate all passengers and 67% of the passengers died. In this article, we walk through the use of SHAP values to explain, in a detailed manner, why an AI model decides to predict whether a given passenger will or will not survive.