AI is set to be one of the most lucrative opportunities for the channel, as it sits right at the forefront of the enterprise innovation agenda. However, delivering AI is difficult, and CIOs are turning to their partners to provide leadership. It is the ultimate test of a partner’s ability to engage with their customers around strategy and vision, rather than technical provision.
According to IDC, AI – including software, hardware, and services for AI-centric systems – will exceed $US300 billion by 2026 at a CAGR of 26.5 per cent. This makes it one of the areas of most rapid expected growth across all IT. With 89 per cent of the CIOs surveyed in the recent Foundry 2022 State of the CIO report saying that their roles were more digital and innovation-focused now, it is clear that AI is seen as a pathway to meet that outcome.
However, 70-80 per cent of AI projects fail. The reasons for this vary greatly, from a misunderstanding of the expected performance of AI, to poor change management, and, most commonly data. A lack of data, or poor data quality, can result in poorly “trained” and ineffective AI. Just as digital transformation experiences a high failure rate and organisations look to their partners to address those challenges, so too will partners be the answer to AI challenges for many organisations.
“Partners need to help customers understand that AI is a long-term investment,” Mei May Soo, Dell Technologies Director of Data Science AI said in an exclusive interview with Foundry. “One cannot expect that an organisation will be able to implement AI in every part of their business immediately. Artificial intelligence is not a tool. It's not software. It's a mindset. A deliberate design centred around behavioural science, and it’s important for the partners to help customers rethink processes and how AI will impact the business so AI can be layered into existing decision-making processes.”
How partners can engage strategically with their customers around AI
For partners that want to help take their customers on an AI journey, there are several key discussion points to engage with them strategically on:
- The ultimate success of AI relies on data
- It is difficult to resource an AI strategy in the current skills climate
- Understand that ethics in AI is a critical subject
AI is built on data, and the quality of data means everything to a successful AI implementation. Many organisations need to find ways to first break down the data silos and improve data and systems architecture. This will enable them to better confirm the quality and consistency of their data.
The skills shortages being felt across most of IT are impacting AI too. For now, embracing large-scale AI solutions is probably not viable as the organisation will lack the data science and IT skills required for them. Instead, the most effective approach to AI is to take a longer-term view, and start with small, easily managed applications. It’s important to make sure that those applications are successful and show a strong ROI, so that the organisation’s appetite for AI continues to grow, rather than wane.
From concerns around privacy and data to protecting against bias and ensuring that the decisions that AI makes are honest, fair and equitable, ethics is a major discussion point in AI. For partners, it means making sure that their customers understand the direction of these discussions. They should also take steps in AI with the assumption that there may be strict regulations in the future. For that reason, paying close attention to ethical best practices around AI is critical now.
While these are all genuine challenges and roadblocks that will make embracing AI difficult for some organisations, according to May Soo, the ROI alone justifies the effort. “When selling AI at any time, keep an emphasis on the return on investment both in the short and long term,” she said. “AI adoption can bring about significant cost reductions, as well as new opportunities for revenue generation.
“For our partners to sell AI successfully in the current economic climate, we recommend that instead of giving an overwhelming picture of AI in general and what it can do for humankind and businesses start with a single problem relevant to the customer, and then gain credibility from that success.”
Those organisations that are not able to scale to embrace AI will find themselves at increased risk of disruption moving forward, as AI starts to automate so much of the workload. CIOs are aware of this, but often struggle to understand the most effective path forwards. For partners, this is the biggest opportunity to engage deeply with customers since digital transformation itself and will be a key focal point for much of the IT budget across all sectors in the years ahead.