The Generative AI Revolution
Robert Griffin
COO at SeedSpark | 20+ Years in Tech, Healthcare, & Banking | Driving Growth, Profitability, and Governance | Cybersecurity Expert | Championing Client Experience | Passionate about Tech-Driven Business Strategy ??
Navigating Sustainability and Strategic Adoption for SMBs
The advent of generative artificial intelligence (AI) in recent years has sparked a technological revolution, promising to reshape industries, enhance productivity, and redefine the way we all learn and work.
For small and medium-sized businesses (SMBs), generative AI’s value proposition is in driving further operational efficiency, sustainable growth and competitive advantage with cutting-edge capability. However, many SMBs face challenges in making a case for gen AI, such as limited resources, intense competition, and limited expertise to tackle the complexity of such tools.
Integrating generative AI with the help of an IT partner, such as a managed service provider (MSP), is one option SMBs can take to address these pain points, as they can implement gen AI with proven expertise to manage the strategic adoption on your behalf. However, there are several general considerations, such as sustainability, which you and your team can assess ahead of time to ensure that generative AI solutions make sense for your use cases today.
Generative AI: Navigating the trends, and key considerations
Generative AI is experiencing rapid growth, with applications extending across industries such as content creation, customer service, and product design. For SMBs, this means access to powerful tools that can enhance efficiency and innovation without needing extensive resources.
Current trends show increasing adoption rates among SMBs due to the technology's ability to automate tasks, personalize customer interactions, and provide deep data insights, while future projections indicate that gen AI will become even more integrated into daily operations, driven by advancements in machine learning algorithms and decreasing costs of AI technologies.
Here’s a breakdown of some of the most prominent and latest reports on gen AI adoption:
●????? According to a 2024 survey by Gartner, 29% of 644 enterprise organizations across Europe, North America, and the United Kingdom said they have deployed and are using generative AI.
●????? According to a late 2023 report by SMB Group, 55% of respondents in its survey of adoption rates of AI among 744 SMBs revealed they are already exploring generative AI platforms, such as ChatGPT, while 27% are already using the technology for ‘concrete business tasks’.
●????? A survey of 2,800 technology professionals in the Generative AI in the Enterprise report by O’Reily revealed while there is growing adoption, 53% of respondents cited that identifying appropriate use cases, and 38% cited legal issues, risk and data compliance as being major bottlenecks for their organizations to successfully implement gen AI.
As these tools become more sophisticated and user-friendly, SMBs will find it easier to implement AI-driven solutions, leading to enhanced competitiveness and growth opportunities.
However, for the moment, SMBs should carefully consider whether now is the right time to invest in gen AI for their specific use cases, given the ongoing maturation of this evolving tech. Timing your deployment with your current business requirements and in-house IT capability is crucial to ensure a long-term strategic adoption rather than a deployment plagued with issues.
Some key factors influencing your SMB’s decision that you should address include:
●????? Technology readiness: Assess if current generative AI solutions meet the specific needs and operational requirements of your business and whether your current IT posture (cloud computing or on-premises infrastructure, cybersecurity, data analytics, cyber awareness training, etc) can adequately support and complement the on-boarding of new and sophisticated AI tools.
●????? Cost implications: Evaluate the initial investment into generative AI against expected ROI, considering whether future cost reductions might make waiting for the technology to mature further beneficial.
●????? Industry adoption: Monitor adoption rates and success stories within your industry to gauge the maturity and effectiveness of AI applications relevant to your business.
In general, we also recommend both your leadership team and workforce get up-to-speed on the fundamentals of generative AI, which you can do using our free online guide, linked below.
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Environmental, economic, and ethical sustainability of Gen AI
One specific area of consideration that has arisen recently is the sustainability of generative AI in terms of environmental, economic, and ethical impacts. While the majority of the conversation, especially in the aforementioned studies and surveys, focuses on other use cases and obstacles, there is an increasing spotlight being put on the topic of sustainability that every SMB should investigate prior to adopting gen AI today. Here is what you need to evaluate:
●????? Environmental sustainability: Generative AI requires substantial computational power, leading to high energy consumption. Your SMB must consider energy-efficient solutions, like optimizing AI algorithms for lower energy use and leveraging cloud services powered by renewable energy sources. Implementing these practices can reduce the environmental footprint of AI operations.
●????? Economic sustainability: While generative AI offers cost-saving benefits, the initial investment and maintenance can be significant for smaller businesses. Your SMB should conduct thorough cost-benefit analyses to ensure a positive ROI. Strategic planning and phased implementation can help manage expenses and maximize the long-term financial benefits of AI adoption.
●????? Ethical sustainability: The use of generative AI raises ethical concerns, including data privacy, algorithmic bias, and job displacement, which you need to be knowledgeable about to meet modern-day compliance standards. Your SMB should adopt transparent data practices, actively work to eliminate biases in AI models, and consider the broader social impacts of AI deployment. Building an ethical framework around AI use, especially ahead of your official adoption of the technology, can foster trust and ensure responsible innovation in the long term.
These considerations will ultimately guide your small business to make better-informed decisions about your potential generative AI adoption and ensure that it is sustainable and strategically sound.
Real-world case studies of generative AI
The applications of generative AI are vast, and many SMBs and enterprises are still assessing the overall impact the technology has had on their business operations at the time of this article.
Many official studies by advisory bodies, such as SMB Group, provide some helpful examples of how generative AI solution vendors have tailored their AI solutions to SMB needs and use cases. Here are some cited in the report to provide your SMB with a better idea of its potential:
●????? AI-powered analytics: These tools enable SMBs to interpret complex data, identify patterns, and make informed decisions without requiring data scientists. Advanced data analysis becomes accessible to businesses with limited resources, empowering them to leverage insights for strategic growth.
●????? Customer relationship management (CRM): AI integration in CRM systems has allowed many SMBs to analyze customer data, predict trends, and personalize interactions to enhance sales forecasting and help them better understand customer needs, driving more effective engagement.
●????? Customer service: AI-driven chatbots and virtual assistants have provided multiple SMBs with the ability to offer 24/7 customer support, reducing the need for extensive staffing. These solutions enhance customer satisfaction by delivering prompt and accurate responses to inquiries.
●????? Financial forecasting: AI-driven forecasting tools assist many SMBs in predicting cash flow, managing budgets, and making informed financial decisions with greater speed and accuracy. This improves financial planning and operational efficiency.
●????? Supply chain management: AI solutions in supply chain management assist several small and medium-sized businesses in improving their inventory levels, forecasting disruptions, and recommending solutions.
It’s clear there are many current-day use cases for generative AI, across multiple sectors, for SMB organizations. But, as with all technology platforms, there is one more important consideration to address before you move toward adoption - whether your small business has the internal expertise and IT resources to handle such a complex deployment of gen AI.
Why managed services is your next step for generative AI
Whether you are in the early stages of assessing the generative AI revolution (considerations, trends, use cases) or further along your journey (preparing for deployment), your SMB should review your current IT posture and in-house capability and address whether external expertise via managed service providers is necessary to assist in your strategic adoption of the tech.
If you are looking for an MSP partner to help you adopt generative AI following best practices, speak to the team at SparkNav and learn today how our generative AI solutions package can bring your SMB up-to-speed.