By Gary Pickford, Managing Director, Tarsus Distribution
Artificial intelligence (AI) is already hard at work in many large enterprises for applications ranging from detecting fraudulent financial transactions to hyper-personalised marketing. But up until recently, the technology has been complex and too specialised for small and medium businesses (SMBs) to adopt.
According to the IBM Global AI Adoption Index 2022, larger companies are twice as likely as SMBs to have actively deployed AI as a part of their business operation. Bigger enterprises are 60% more likely than smaller companies to have a holistic strategy for how they will use AI across their organisation.
Barriers to successful AI adoption include limited AI skills, expertise or knowledge; cost of AI services and technology; lack of tools or platforms to develop models; difficulty in scaling and integrating projects; and too much data complexity. These obstacles are especially daunting for SMBs with limited resources.
But we can expect the transition towards AI-as-a-service (AIaaS) models to rapidly erode these barriers for SMBs. As we’ve seen with the breakthrough success of generative AI tools like ChatGPT, DALL·E and Bard, the technology is rapidly becoming far easier to use as well as more accessible via subscription billing models.
Many SMBs are already experimenting with these tools and are ready to do more with AI. Traditional hardware vendors and hyperscale cloud providers, meanwhile, are commoditising many of the cloud, edge and on-prem AI solutions they have packaged for the enterprise market via pay-per-use models.
Some of the solutions in the pipeline are truly remarkable, using high-performance computing infrastructure of such power that only a handful of organisations in the world could afford them in the past. They also enable SMBs to avoid much of the intensive development work it used to take to create a sophisticated AI solution in the past.
AIaaS options will enable SMBs to deploy and scale AI for a range of applications without needing to make massive investments in specialised technology platforms and integration or spending budget on rare, expensive data science and cloud architect skills. SMBs will be able to use pre-trained AI tools to fast-track and simplify their deployments of AI services and solutions.
Potential applications for AI in SMBs are numerous. Chatbots and even virtual assistants can be a powerful way to offer round-the-clock customer service, with the AI learning to provide better answers to customer queries as it interacts with more customers. Other powerful applications for AI can be found in automating IT processes to free up the IT team’s time.
AI can also be paired with the Internet of Things (IoT) for compelling applications at the edge. For example, IP-based video cameras and AI-powered video analytics can recognise humans, vehicles, objects, and events, and then alert a security company if something looks out of place.
AI is likely to explode in the SMB sector as business owners and leaders recognise its potential to enable them to do more with fewer resources. Resellers and systems integrators have a unique chance to tap into this fast-growing market. Consulting, integration and advanced data management services will be in high demand. The most promising avenues lie in offering AI-driven solutions that are designed to solve specific industry or functional pain points. Tools that can be deployed quickly and that lead to immediate customer experience improvements or efficiency gains will find favour in a tight economy.
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