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GenROI
Commercializing AI in the Channel
However, there is AI money to be made in the channel today and the groundwork needs to be laid for longer-term prospects too. We often hear the latest sweeping changes heralded by AI being compared to past industrial revolutions sparked by steam power or electricity. This is true in the sense that AI’s impact will be similarly ubiquitous. However, in other ways the AI era will be more like the enlightenment period than any sudden revolution. An incremental, multi-generational march of progress. The power of AI isn’t bound up in a single innovation – not even ChatGPT – it is in the use cases and applications that accompany countless innovations. The channel will need to have a two-pronged approach to their AI strategy. One short and one long.
T
he channel has been talking about AI for decades – even monetizing it in some cases. However, the recent acceleration of GenAI capabilities has created a huge wave of AI hype and investment.
Much of the current financing, and return, is on the left of the maturity curve – in AI semiconductors, infrastructure and large language models. This is driving growth in share prices but not yet meaningful revenue for most technology companies.
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Partners with extensive data or solution backgrounds are realizing immediate impacts. However, many customers are in experimentation mode. While, for most partners, this is a ‘wait and see market’, overall, partners are cautiously optimistic. Some are generating revenue today and almost all expect AI-driven revenue to grow rapidly within 12 months. There are echoes of the evolution of the market during cloud partner development. There are leaders, but that is a limited set of partners. The channel needs help understanding the real and most immediate opportunities for AI, without it distracting the core business in the short term, as well as how solution providers are leveraging AI technology to increase revenue and improve their operations. This report guides channel leaders on how to be prepared for the impact of AI on their channel business, and how to plan for growth.
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PED, the consulting arm of CRN parent The Channel Company, conducted an extensive AI channel impact study. A survey of 241 respondents from the channel-at-large, supported by 20 partner and
10 vendor interviews.
Executive summary
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The AI era will be more like the enlightenment period than any sudden revolution
NVIDIA CEO Jensen Huang talks about four waves that will drive AI adoption and growth in the market: initial AI model training and infrastructure build-out, large scale enterprise adoption of AI, increased AI usage in industry use cases, and widespread AI adoption by governments. As we emerge into the second of these waves, we can expect initial opportunities to drive client technology refreshes in hardware and software, as well as integration services. Larger scale deployments in specific industry use cases will follow.
AI is a positive catalyst for conversations, even more so than cloud
Its detailed view of the AI state of play in the channel shows us where current AI opportunities lie and how partner strategies must accommodate them. The richest soil for partners is amongst large entities investing in AI infrastructure. This market is growing exponentially. Partners selling to large companies are responding in kind by investing aggressively. One large, services-led MSP revealed, “In the last three to six months, I’ve seen a solid uptick of customers saying, ‘I have been asked to put together our AI posture report, can you help?’.” Meanwhile, partners selling to SMBs are primarily investigating. There is confidence this will translate to revenue growth over the next two years. One small, services-led MSP stated, “We’re having lots of open conversations with customers and engaging more often now. AI is a positive catalyst for conversations, even more so than cloud.”
CONCLUSION AND sponsor INFO
AI ROI obstacles
Business models and use cases
AI impacts and investment
INTRODUCTION AND Executive summary
Predictions for the next 12 to 24 months are far more optimistic. Forty per cent expect significant positive impact and just five per cent a negative one. The question then becomes, ‘how do we bridge this gap?’ Any meaningful answer will demand change across people, processes and technology – all reflected in go-to-market strategies. This means investment. While half of those surveyed are investing cautiously, 22 per cent are laying down their chips more purposefully. The remaining 28 per cent, many of them smaller partners, are waiting to see how the market evolves before committing.
J
ust 13 per cent of partners surveyed have seen AI have a significant positive impact on their business so far – though a further 49 per cent has seen a positive impact of some degree. One-in-three even
relayed a negative impact. This speaks to the huge challenge faced by partners in navigating this AI era.
Fig. 1: Impact of AI technology on overall business
Fig. 2: Investment strategy
Larger partners (those making over $100M in annual revenue) are three times more likely to be investing aggressively. This funding is most regularly being applied to lab and demo centers, hiring and training, and customer education and workshops. Blockers to investment include lack of AI experience, the need for clarity around the opportunity, smaller customer bases, and ongoing investigations into customer solutions and use cases. End user organizations reflect these adoption attitudes, in many cases dependent on their channel partners to help inform and implement their AI strategies.
Fig. 3: End customer implementation status
About the sponsor
Conclusion
28%
Not Investing Yet – Wait and See
Cautiously Investing
50%
Aggressively Investing
22%
No plans
Investigation/ Experimenting
Limited Deployment
Extensive Deployment
Over the Next 12-24 Months
13%
So Far to Date
2%
49%
3%
33%
40%
38%
14%
5%
Significant Positive Impact
Minimal Positive Impact
No Impact
Negative Impact
Not Applicable
BUSINESS MODELS AND USE CASES
Perhaps most appealing today, at least to MSSPs and CISOs, are security and risk management use cases. We often hear about the data privacy and security risks associated with AI. While those risks are very real, AI automated defense shows more promise than AI automated attacks. AI in cybersecurity is likely to lead to a much-needed democratization of defensive capabilities, and better governance and security practices, making it harder for threat actors to succeed. While the need for human oversight and intervention remains, the ability for AI to maintain 24-hour monitoring and rapid detection and response is invaluable. For MSSPs looking to employ AI to scale their cybersecurity business, this represents an attractive route to growth without an equivalent scaling of costly headcount. As one small consulting and service provider puts it, “The opportunity is simple – we need to use AI to be able to understand the old attacks and to adapt to the new."
S
oftware and analytics services are a natural fit for AI. Many of the greatest productivity gains and business cases play to AI’s ability to crunch large amounts of data, identify and act on trends, or
automate large volumes of relatively simple but resource intensive tasks. Two-thirds of those surveyed are seeing a positive impact to one extent or another in these areas. These same strengths apply to platform and data management services, which are not far behind.
CONTENT
Fig. 4: Solution offerings – AI impact in the next 12 months
Fig. 5: Expected impact of AI technology on specific business areas in the next 12 months
These product area benefits are largely reflected in the business models seeing the most positive impacts from AI today. Nearly two-thirds of managed services businesses are seeing some positive impacts – 1-in-5 significantly so. Cloud services businesses aren’t far behind. These are both mature models with rich ecosystems that have innovated to integrate AI into their product stacks. Fifty-six per cent of AI pioneer solution providers – those most invested in AI – believe cloud will be significantly positively impacted thanks to hyperscaler partnerships. As the AI space matures, application development businesses will reap the rewards of greater industry-specific deployments, and resell businesses will be able to more readily demonstrate genuine business outcomes. This is particularly true of larger, product-focused partners that have enterprise class customers.
Fig. 6: AI pioneers (partners leading the way in terms of investment)
Other
Security and Risk Management
Software and Analytics Services
Platform and Data Management Services
Industry Based Solutions
Infrastructure Optimization
32%
31%
34%
43%
35%
17%
44%
39%
16%
Managed Services Business
Cloud Services Business
Professional Services Business
Application/Solution Development Business
Products Resell Business
21%
42%
15%
20%
19%
24%
18%
27%
1%
26%
56%
59%
41%
All Others
AI ROI OBSTACLES
A
s we saw with cloud transformation, any rapid, sweeping technology change is accompanied by as many challenges and questions as it is benefits and answers.
Fig. 7: Biggest AI investment inhibitors
Figure 7 shows the hurdles faced by channel partners. End user sentiment mirrored these positions, with the exception of ‘cost to implement’, which ranked second. The leading takeaways are that AI technology will make it harder to protect against digital threats, current AI solutions are often not accurate enough to use, or the output is not easily explainable. To put this in context, one service provider reasoned that AI-based solutions need to be, “90 per cent accurate in identifying issues with Networks.” For others, AI technology is evolving too quickly to make investment decisions. Larger organizations and AI pioneer partners were around 50 per cent more likely to cite technology rate of change as a top three inhibitor. One large VAR stated, “We need to be cautious because the market is changing very fast.”
Top 1
Top 3
Top 5
23%
12%
11%
10%
Cybersecurity
Technology Accuracy
Technology Rate of Change
Intellectual Property Infringement
Personal Individual Privacy
Regulations
Competitiveness
Talent HR
Internal Usage
6%
9%
7%
ABOUT THE SPONSOR
OpenText Cybersecurity provides comprehensive security solutions for companies and partners of all sizes. From prevention to detection and response, to recovery, our unified end-to-end platform helps customers build cyber resilience via a holistic security portfolio. Powered by actionable insights from our real-time contextual threat intelligence, OpenText Cybersecurity partners benefit from an end-to-end layered security stack that helps simplify your business. As one of Microsoft’s top indirect CSPs, OpenText Cybersecurity provides partners the tools needed to grow with the Microsoft AI Cloud Partner Program, maximize rebates, and navigate complexities along the way.
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Understanding the AI opportunities today, and in the mid-to-long-term is a key starting point. At the heart of this education is the ability to differentiate between them. Vendors and partners must pursue strategic partnerships within the channel that are aligned with their AI maturity and capabilities. Much of this activity will be a catalyst for yet more M&A activity. These partnerships must then be supported by materials and education sessions that communicate best practice, use cases, and business outcomes. This all signals a paradigm shift in the channel – at least as significant as that initiated by cloud innovations. Channel strategies and partner programs will have to evolve to accommodate these significant changes. That said, AI will also enable partners to do what they’ve always done, only more effectively: foster partner relationships, add value, provide timely partner support, and streamline tasks outside the core business. The winners and losers within the channel will be dictated by when and how AI investment is applied, and the go-to-market framework around it. The only certainty is that investment must happen. In other words, disrupt or be disrupted.
uccessful monetization of AI in the Channel will require close collaboration and a systematic evolution of channel programs, from end-to-end.
CONCLUSION
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