The generative AI gold rush has begun, but the question now is, “who will pay the bill”?
Tech giants like Microsoft and Google are realising the immense costs associated with AI and are exploring strategies to shift these expenses onto consumers. As leaders and business owners, we need to understand these shifts and prepare for a future where access to AI might come at a premium. This post dives into the implications, challenges, and opportunities arising from this evolving AI landscape.
5?Key Learnings for Business Owners and Leaders
- AI Isn’t Free:?The promise of AI has been enticing, but it's crucial to recognise the substantial financial investment required to build and maintain these systems. There are infrastructure costs to consider for any business thinking about creating and delivering AI solutions.
- Cost Shifting to Consumers:?Companies are likely looking at a hybrid model where some AI capabilities are delivered in the cloud (expensive servers in data centres) and some are executed by user-based machines. Be ready for this scenario!
- Edge Computing is on the Rise:?Edge computing, where AI processing happens on users' devices, is becoming a strategic necessity for tech companies.
- Hardware Matters:?Edge-based AI opens the way for those companies to push us to buy new devices and upgrades to access AI features that would normally happen in data centres.
- Competition can lead to innovative AI: Innovation could become the norm and open the way for new possibilities in the business world.
5?Challenges for Businesses to Prepare For
- Budgeting for AI Integration:?Organisations must anticipate the increased costs associated with integrating AI into their operations, including potential hardware upgrades for employees.
- Addressing the Digital Divide:?The shift to edge computing could exacerbate the digital divide, as access to AI becomes increasingly tied to device ownership. Businesses need to be mindful of equitable access to AI-powered tools and resources.
- Managing E-Waste:?The push for frequent hardware upgrades could lead to increased e-waste, posing environmental challenges. Businesses should explore sustainable device management practices.
- Protecting User Privacy:?Edge computing raises questions about user privacy, as AI processing occurs directly on personal devices. Businesses need to implement robust data protection measures.
- Staying Agile:?The AI landscape is rapidly evolving. Organisations need to remain agile and adaptable to changing cost models, technological advancements, and user expectations.
5?Insights for Organisational Growth
- Business model shift: This could happen to any kind of business in any industry where prices will rise.
- Privacy protection: If more AI is used, it could mean less privacy.
- New AI capabilities: AI needs to be developed more effectively in order to continue its innovation journey.
- Environmental concerns: More demand for hardware products could lead to a devastating path for e-waste.
- Increased competition: More innovative companies could benefit from a competitive landscape.
Conclusion: Navigate the Evolving AI Landscape
The AI revolution is upon us, but the path to adoption is filled with challenges and uncertainties. As the costs of AI rise, businesses must prepare for new models, increased expenses, and potential shifts in how AI is delivered and accessed. By staying informed, planning strategically, and prioritising ethical considerations, we can navigate this evolving landscape and unlock the transformative potential of AI for all.
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Authored and published by Mitchell Filby, Managing Director at First Rock Consulting.
Sales Leader | Digital Transformation Advocate | Champion of Exceptional Customer Experiences
8 小时前How long before Google pushes for paid Gemeni responses like they do for Adwords in normal search? If you want the AI to push your product in the response pay for it.....
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9 小时前Mitchell Filby Artificial Intelligence must be evaluated in a similar way to other organisational decisions; what is the return on investment? Will AI allow my organisation to do more with current resources? Does that difference make it worthwhile? AI has to a large extent been free up to now as our value was to train the models. Now the Googles, Microsoft's etal are moving to a commercial model where those of us who benefit pay for the privilege. The value of the specific application within the organisation will determine if it makes sense to employ systems intelligence, in most cases it does.