Companies and growing companies are certainly doubling the future of AI, but what are the practical paths to operating these tools? What does the channel partner mean?
The data certainly shows that corporate leaders view AI as a business priority and are even transformational opportunities. One recent study suggests that UK organizations will increase AI investments by more than 25% in 2025. A survey of 1,000 purchase decision makers in the UK, US, France and Dach regions shows that 92% of people supporting annual budgets have an astounding 92%.
In addition, businesses are planning lean operations using AI. Almost half of the survey (46%) predict that a key outcome of AI implementation is cost savings.
That's Enterprise AI Vision, but what is the practicality of making it happen?
Persistent obstacles to AI adoption
Despite corporate ambitions and highly focused budgeting, research studies have identified deep-rooted security, infrastructure and talent challenges that pose real obstacles to AI implementation plans.
In our study, one in three (34%) organizations believes that security and privacy concerns are obstacles to successful AI adoption, and, worse, that data is effectively integrated into AI demands. These are the weaknesses of endemic security and data management that global-level research has already highlighted.
With the prospect of integrating these sophisticated tools into business processes and workflows, more than a quarter (27%) of businesses believe there is a lack of skilled people to manage them well.
Expert guidance you need from the channel
Given these gaps between the company's AI aspirations and the team's ability to deliver them, the growing demand for strategic partners and integrators to help ambitious organizations adopt AI and jump to greater business efficiency and innovation, solving cloud immigration tasks that fall below the integration of complex infrastructure and the success of AI programs.
This preference for experts and trustworthy advisors also has roots in today's customers who have moved from a volume approach to technology acquisition and instead seek strategic, future-looking vendors and insightful channel partners. Unleash these projects that support the channel market approach while supporting executive teams and creating robust business cases for AI investments.
C level and IT decision
The openness of companies to external inputs is enhanced by the outstanding factors revealed in our study. The growing role of C-level executives in setting an organization's AI vision. Our data show that AI project decisions are equally balanced between C-Suite (38%) and IT (39%). This “shared” C-level and IT business leadership, and technology priorities of transformation drive the demand for a wider strategic perspective and wider options of channel support.
Demand for insight
Our research found that organizations in all industries are committed to preparing the AI technology stack. We found that the average organization is already spending 18% on modernizing cloud infrastructure to drive AI initiatives. Even cash-constrained sectors such as healthcare (14%) and public sector (11%) are bolstering their investments as many AI services are available through the cloud or through the major cloud providers.
But for now, the focus of company leaders is to understand the possibilities of AI. Our data shows that only one in four AI projects requires a measurable ROI. The starting point suggests that, rather than fostering early implementation as a way to deliver transformative business outcomes, we are investigating and reducing the capabilities of AI tools.
The opportunity beckons
With senior executives prioritizing AI plans, research suggests that there are exciting and long-term opportunities for channel partners that help organizations access AI products from global technology providers, and channel partners that can help resellers deliver the strategic needs of companies and flexible economics in the rapidly evolving age of AI. This is good news for VARs who are bringing “Value For Value” back to truly helping customers. In particular, it is a challenging and important task of integrating infrastructure and data platforms for game-changing capabilities in AI.
