Taking the time to make a use case for AI will propel companies further and improve the return on investment in this fast-changing technology. The market is officially three years post ChatGPT and many of the pundit bylines have shifted to using terms like "bubble" to suggest reasons behind generative AI not realizing material returns outside a handful of technology suppliers. In September, the MIT NANDA report made waves because the soundbite every author and influencer picked up on was that 95% of all AI pilots failed to scale or deliver clear and measurable ROI. McKinsey earlier published a similar trend indicating that agentic AI would be the way forward to achieve huge operational benefits for enterprises. At's Technology Council Summit, AI technology leaders recommended CIOs stop worrying about AI's return on investment because measuring gains is difficult and if they were to try, the measurements would be wrong. This places technology leaders in a precarious position-robust tech stacks already sustain their business operations, so what is the upside to introducing new technology?

Small and medium sized businesses often struggle with data driven decision making do to a lack of advanced analytics tools, especially in African countries where they make up a majority of the workforce. Though many tools exist they are not designed to fit into the ways of working of SMB workers who are mobile first, have limited time to learn new workflows, and for whom social and business are tightly coupled. To address this, the Dukawalla prototype was created. This intelligent assistant bridges the gap between raw business data, and actionable insights by leveraging voice interaction and the power of generative AI. Dukawalla provides an intuitive way for business owners to interact with their data, aiding in informed decision making. This paper examines Dukawalla's deployment across SMBs in Nairobi, focusing on their experiences using this voice based assistant to streamline data collection and provide business insights

In the field of business data analysis, the ability to extract actionable insights from vast and varied datasets is essential for informed decision-making and maintaining a competitive edge. Traditional rule-based systems, while reliable, often fall short when faced with the complexity and dynamism of modern business data. Conversely, Artificial Intelligence (AI) models, particularly Large Language Models (LLMs), offer significant potential in pattern recognition and predictive analytics but can lack the precision necessary for specific business applications. This paper explores the efficacy of hybrid approaches that integrate the robustness of rule-based systems with the adaptive power of LLMs in generating actionable business insights.

At the Microsoft Inspire partner event today, the Windows maker announced pricing for its AI-infused Copilot for Microsoft 365. The suite of contextual artificial intelligence tools, the fruit of the company's OpenAI partnership, will cost $30 per user for business accounts. In addition, the company is launching Bing Chat Enterprise, a privacy-focused version of the AI chatbot with greater security and peace of mind for handling sensitive business data. Revealed in March, Microsoft 365 Copilot is the company's vision of the future of work. The GPT-4-powered suite of tools lets you generate Office content using natural-language text prompts.

Ever since ChatGPT captured our imaginations, people have been contemplating its pending impact on the business world. This week these thoughts became a reality, with Google and Microsoft embedding artificial reality (AI) features into their business productivity suites. Microsoft took another major step by releasing AI Copilot for Power Apps, Microsoft's low-code platform. Power Apps can connect far and beyond the Microsoft ecosystem, with almost 1,000 built-in connectors to everything from Salesforce to on-prem and Amazon Web Services. With one swift move, AI has been integrated into the day-to-day workflows of the world's largest organizations. This is an amazing achievement, and other low-code/no-code platforms will surely try to catch up quickly.

Humans are hard-wired to dream, to create, to innovate. Each of us seeks to do work that gives us purpose -- to write a great novel, to make a discovery, to build strong communities, to care for the sick. The urge to connect to the core of our work lives in all of us. But today, we spend too much time consumed by the drudgery of work on tasks that zap our time, creativity and energy. To reconnect to the soul of our work, we don't just need a better way of doing the same things.

Data Science offers lucrative career opportunities in this day and age. Data scientists produce actionable business insights using data and implement mathematical algorithms to solve complex business problems. In fact, Amazon product recommendations, Netflix movie suggestions, Google Maps traffic predictions are some of the prime examples of data scientist work that we use every day in our lives! Data scientists' algorithms are helping many companies generate more revenue and enhance the customer experience of their products and services. Owing to these reasons, everybody aspires to be a data scientist these days.

While ransomware attempts to exploit your data for hackers' financial gain, for many businesses, the worst-case scenario is that their financial data becomes compromised. A financial data breach can cause your audience to distrust you or blame you for exposing their sensitive data to hackers. There are material and reputational damages to your business model. Fortunately, AI can bolster your cybersecurity efforts by keeping financial data safe. Sophisticated hackers have a variety of tools in their arsenal when it comes to obtaining your financial data.

Technology is continuously updating at such a fast pace which it is might be quicker than light. A programming language that is making the rounds today might be obsolete by the next couple of days. As more money is invested in the development and research, professionals and computing scientists are continuously tweaking and enhancing current technologies to maximize them. Thus, new technologies and programming language, patch, library, and plug-in are released per hour. To maintain this fast pace of development, you need to keep on knowing the newest technology ideas.

Along with data and analytics, the focus on continuous improvement remains a constant in the business world. Recent market disruptions have only emphasized the need for businesses to optimize their processes and core functions moving forward. Artificial intelligence is one tool companies are turning to when achieving greater efficiency within their operations. Let's explore how AI is transforming the way we do business, from data cleaning to the customer experience. Let's get straight to the point.