- April 23, 2024
- Posted by: Channelnomics
- Category: Blogs
Channelnomics has identified seven significant challenges that will impede the adoption of artificial intelligence systems. The good news is that they’re also great opportunities for vendors and partners.
Market analyst firm IDC forecasts an impressive 55% compound annual growth rate (CAGR) for the artificial intelligence market from 2024 to 2027. However, it’s worth noting that this growth could be even more rapid if barriers to customer adoption and deployment weren’t hindering the pace of artificial intelligence uptake. This potential for accelerated growth should inspire optimism and excitement among vendors and partners alike.
Generative Pre-trained Transformer (GPT) products such as ChatGPT, Microsoft Copilot, and Google Gemini aren’t just tools; they’re catalysts sparking the imagination of businesses and individuals. These tools, by revolutionizing content creation, data analysis, and automated customer experiences, are making the seemingly impossible possible. However, it’s important to note that GPTs are just the tip of the iceberg in the artificial intelligence revolution.
In a survey by Channelnomics and channel marketplace Pax8 of end users worldwide, most businesses said they want AI tools that deliver better predictive analytics, machine learning in their automated processes, and richer communications tools. While it’s easy to rattle off a list of tools, making them an operational reality is much harder.
Through extensive research of vendors, channel partners, and end users, Channelnomics has pinpointed seven significant challenges currently impeding AI adoption and growth. However, these challenges, far from being roadblocks, present unique opportunities for the channel to leverage its expertise and resources, paving the way for success in the AI market. This understanding should empower vendors and partners, highlighting their potential to overcome these challenges and thrive in the AI landscape.
Let’s dive into each.
- Insufficient Infrastructure
Challenge: Businesses adopting artificial intelligence systems and solutions must update and upgrade their IT infrastructure—servers, storage, security, and networking gear—to accommodate the various applications’ high-capacity workloads, data retention, and security needs. Many PCs will also need replacement to accommodate advanced AI use cases.
Potential Solution: Equipment replacement and upgrade programs with customers. Hardware vendors are developing new AI-capable products that will greatly increase the efficiency of AI processes and improve user experiences. IDC estimates that up to 30% of artificial intelligence investments will go toward infrastructure improvements.
- Poor Data Availability, Hygiene, and Integrity
Challenge: Vendors and ISVs tell Channelnomics that many businesses — even the most sophisticated enterprises — don’t have the data, data access, or data with integrity (true data) to form the foundation for training and operationalizing AI systems.
Potential Solution: Data hygiene and management are huge opportunities for partners that have professional service capabilities to aid customers in identifying data sources, providing data structures that align with AI systems, and managing databases. - Lack of AI Talent
Challenge: A talent war for qualified artificial intelligence talent is already underway. Technology vendors and non-tech companies are racing to hire AI and data science professionals to design and operate AI systems. But the AI talent pool is shallow. The current pool — even when sourcing internationally — is insufficient to meet current and future demand.
Potential Solution: AI-as-a-Service (AIaaS) will become a huge business for partners that can amass the talent pool to deliver resources at scale. Just as the channel gained by providing managed services that spread resources across multiple accounts and fractionalized costs, artificial intelligence services will create the opportunity to deliver AI applications and resources to multiple customers with an aggregated talent pool. - AI Security Requirements & Threats
Challenge: Traditional security and data protection technologies still apply in the artificial intelligence world, but the security needs of AI systems face different operational requirements and threats. The data used for AI must be segregated and have role-based access controls. New threats aimed at accessing and compromising AI systems will necessitate new controls to protect data confidentiality, integrity, and availability.
Potential Solution: Partners with security practices will find new opportunities to help end users identify security needs, implement new AI security controls, and manage their AI data protection. AI security needs will also draw new sales and service opportunities for conventional technologies. - Undefined Use Cases & Reference Architectures
Challenge: The use-case challenge is complicated. Many artificial intelligence use cases exist, but many are the applications of chatbots that automate customer service, technical support, or worker productivity. Others are specific use cases for individual applications, such as image and video creation. Examples of use cases for predictive analytics and machine learning processes exist but are often bespoke and not repeatable. Currently, businesses can envision the application of AI in their operating environments, but they don’t know where to start.
Potential Solution: Vendors and partners are already developing use cases for AI systems in their customer environments. They can develop these cases and help customers assess their needs, develop practical systems, and demonstrate ROI. - Not Enough Power & Real Estate
Challenge: The world is adding three new data centers daily to meet the growing need for cloud solutions and artificial intelligence systems. Even at that rate, the demand is outstripping the market’s ability to create capacity. The culprits are limited electricity supply-grid capacity and insufficient real estate near power sources — particularly renewable-energy production centers.
Potential Solution: Partners will find strong opportunities for selling and supporting energy-efficient data center equipment and power and cooling systems. While upgrading equipment with better power consumption ratings will help slow the need for new infrastructure, it won’t completely solve the problem. The inability of customers to build and expand on-premises data centers will also create new opportunities to resell co-location and public cloud services. - AI Ecosystem Development
Challenge: No company can meet all of a customer’s artificial intelligence needs, not even the hyperscalers. Addressing end customers’ AI needs takes a collection of companies working together to share resources, expertise, and capacity. In other words, the ecosystem is effective in co-selling and co-supporting. The challenge is that these relationships are often hard to form and maintain.
Potential Solution: Many vendors are creating registries and databases for partners to identify and connect with other qualified and complementary companies to build relationships that align with the needs of their mutual customers. Forming ecosystem relationships is essential to meeting market demand for complex AI systems. Partners should leverage their vendors’ and distributors’ connections and recommendations to identify potential ecosystem partners.
Looking Forward
As the artificial intelligence revolution continues to unfold, it’s clear that technology’s transformative potential isn’t without challenges. The road to widespread AI adoption is paved with obstacles, from technical hurdles to talent shortages and security concerns. However, these challenges also present a unique opportunity for the channel to step up and lead the way forward.
By leveraging their expertise and extensive resources, vendors and partners can become the driving force behind AI adoption, helping businesses navigate the complexities of this rapidly evolving landscape. Whether it’s through developing innovative AI solutions, providing expert guidance and support, or forming strategic partnerships, the channel has a critical role in shaping AI’s future.
The AI market is poised for explosive growth as we look ahead to the coming years. But to truly harness the power of this transformative technology, vendors, partners, and customers must work together to overcome the obstacles to AI success. However, with the right strategies, partnerships, and mindset, there’s no limit to what we can achieve.
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