Small and medium-sized businesses (SMBs) play a vital role in the success of economies worldwide, accounting for two-thirds of business employment. For SMBs looking to harness the power of artificial intelligence (AI), utilising tools already embedded in their daily software is the best starting point. Examples of such AI tools include OpenAI’s ChatGPT, Microsoft’s Copilot, and Google’s Gemini. In addition, we are sharing three surprising ways AI will transform the operations of small businesses, and the relevant tools and how to assess them.

Identifying the right processes for AI automation is crucial for maximizing benefits. This section outlines the AI Process Readiness Assessment: the key steps to identifying and prioritizing automation processes. It includes assessing current workflows, identifying repetitive tasks, and evaluating the potential impact.Once you have identified the target processes, you may consider implementing AI workflow automation software. It involves using AI algorithms within workflow systems to automate complex tasks. AI workflow automation utilizes machine learning, natural language processing, and other technological advancements to accomplish intricate tasks.

According to a recent PwC survey, 61% of U.S. CEOs expect AI to change how their business generates value, making generative AI a top investment priority for most organisations. However, enterprises must turn AI hype into reality to realise this potential. CIOs and other technical leaders should focus on three main areas to sustain the AI momentum: Data Infrastructure, Foundational Models and AI Accuracy.

"Despite the soaring demand, only 10% of AI initiatives are delivering significant ROI." Artificial intelligence (AI) has become a critical driver of business transformation, enabling organizations to optimize processes, make data-driven decisions, and unlock new growth opportunities. Integrating artificial intelligence (AI) into all business areas is crucial for a company to gain or maintain a competitive edge.With the average ROI at 5.9%, research from IBM suggests that certain companies earn a more notable 13% on their AI projects. So, what sets these 13% ROI achievers apart?

Many news articles about AI adoption predict the decline of middle management, suggesting that middle managers are becoming less important. However, what if this perspective is incorrect? AI is a significant aspect of digital transformation and requires middle managers to adapt their teams to new demands in AI-integrated work environments. Not everyone will readily embrace AI, so middle managers must help their teams recognise the advantages of this new technology.

The race to dominate the Artificial Intelligence landscape is intensifying in the rapidly evolving world of technology. Big tech companies, including Microsoft, Amazon, and Alphabet, are not only competing against each other but also investing heavily in promising startups to accelerate their AI initiatives. The world's ten most valuable tech firms are all involved in developing technology for the robotics industry.

Leaders must actively explore and define how AI can redefine their industries. The future of innovation lies in our ability to envision a world where AI’s potential is fully integrated into the fabric of organizational creativity and growth.The key to success lies not in the technology itself but in designing a new native AI operating model to unleash its true value across People & Capabilities, Technology, Culture and Organisation.

Businesses are increasingly recognizing the value of adopting AI to enhance their daily operations.It's important to conduct an AI Health Check across your business, which will allow you to take a comprehensive look at your organization and consider your AI strategy, governance, leadership, culture, and ethical principles. This assessment is required whether you are in the early phases of AI adoption or already in implementation stage.

Similar to other sectors, the retail industry is facing pressures from the rising cost of living, including high inflation and significant interest rate hikes. With expectations of reduced consumer spending, shoppers are opting for more affordable options and cutting back on non-essential purchases. As a result, retailers are forced to find innovative strategies to attract customers and mitigate declining sales. Artificial intelligence offers a range of applications in retail, from enhancing customer service to managing inventory.

Top generative AI use cases for business include advanced chatbots, digital assistants and Coding Assistants. However, a number of industries are also leveraging Generative AI for Process augementation and cybersecurity.

In recent years, natural language processing (NLP) and large language models (LLMs) have been revolutionized by transformer models. However, transformers are inefficient at processing and analysing large amounts of data when running on standard hardware. This inefficiency is causing significant and potentially unsustainable increases in power demand as companies develop and expand infrastructure to meet the requirements of transformers." Researchers are actively exploring new architectures that could potentially replace or augment transformers.

AI orchestration involves managing different AI models' interaction, deployment, and integration within a workflow or system. This technology can assist in redistributing decision-making roles between IT and Line of Business (LOB), reorganizing operational systems, redefining customer acquisition and sales processes, and more. AI orchestration separates models, prompts, and vector databases to create a customized Retrieval Augmented Generation (RAG) framework that can be set up quickly. This approach enables organisations to easily scale their AI initiatives, efficiently managing the deployment and use of AI models and resources. It allows them to adjust swiftly to increasing workloads or changing demands, ensuring optimal performance and resource allocation.

Choosing the right approach to integrate GenAI technologies is crucial in shaping a comprehensive GenAI strategy. As we move into an era where highly advanced AI capabilities are readily available, it becomes essential to plan for their effective use. Organizations have the option to either adopt off-the-shelf GenAI functionalities within their applications or access them via APIs for convenience. On the other hand, more sophisticated strategies tailored to an organization's specific data and objectives can greatly enhance benefits, albeit with increased complexity in customization. Deciding between widespread implementation of basic tools or investing in deeply integrated, advanced capabilities is a pivotal strategic decision.

Quantum computing can revolutionise industries by solving complex problems at unimaginable speeds. It unlocks new possibilities for innovation in fields like cryptography, drug discovery, and artificial intelligence. It proves indispensable in diverse business scenarios, encompassing intricate data analysis, optimisation quandaries, cryptography, and machine learning interventions. Its unparalleled capacity to handle colossal data volumes and execute computations swiftly renders it a crucial asset for finance, cybersecurity, logistics, and pharmaceuticals.

Wine producers are increasingly leveraging robots to streamline various aspects of the winemaking process. From vineyard management to bottling, robots are being utilized to improve efficiency and consistency in production. In vineyard management, robots equipped with cameras and sensors can monitor crop health, optimize harvesting times, and reduce the reliance on manual labour. Within wineries, robots are being used for tasks such as grape sorting, fermentation control, and bottling. These robots can work around the clock without fatigue, leading to increased productivity and quality control. We take a closer look at the use of robots at Freixenet in Spain and Marchesi Antinori in Tuscany.

North American banks are outpacing their European counterparts. They have published 80% of all AI research and filed 99% of all AI patents in recent times. French banks have been more cautious in adopting AI compared to US banks. This is due to stricter data privacy laws, such as GDPR, and a cultural preference for personal relationships in customer interaction.

Small Businesses which have historically been more hesitant to embrace technological advancements, now have the opportunity to spur innovation by collaborating with seasoned professionals from major technology firms. Small businesses are indeed increasingly using AI technologies to make their operations easier, boost productivity, and gain a competitive edge. This shift is seen in the adoption of AI tools like chatbots for customer service, data analysis for personalized marketing, predictive analytics for better inventory management, and automation of routine tasks.

The five tech companies that have a strong AI Strategy and that have invested the most in AI startups in 2023 are Amazon, Google, Microsoft, NVIDIA, and Salesforce. They continue to amplify their focus on artificial intelligence technologies, leveraging vast amounts of data to enhance automation and innovation across various industries. As these firms delve deeper into AI research and development, the potential for transformative solutions and advancements in machine learning remains a key priority on their agenda. We provide insights on their respectiv AI strategies.

Value-based selling focuses on the prospect and their needs rather than the solution you're trying to sell. Value-based selling in B2B entails delving into the distinct requirements and preferences of the business customer and illustrating how your product or service can deliver concrete value while meeting those needs. In contrast to fixating solely on features and pricing, value-based selling accentuates the advantages and results that the customer can anticipate from embracing your solution. We outline the process and tools to leverage.

AI is rapidly transforming industries worldwide as companies aim to optimize their operations and gain a competitive edge. From healthcare to finance, manufacturing to retail, AI is being used to streamline processes, improve decision-making, and drive innovation. According to Microsoft and LinkedIn’s annual Work Trend Index, 84% of Australian workers are using generative AI in the workplace, which is a higher percentage compared to Europe and North America.