By Mark McNerney, Quantexa
Artificial intelligence (AI) and machine learning (ML) technology firms’ channel strategies have become increasingly reliant on strong strategic partnerships and trusted resellers. AI and ML rely heavily on huge volumes of data, making good data providers a requirement for any successful business. It is critical to select best-of-breed companies who can bring data-driven value to the technology platform.
In the same way that oil powers an engine, data is the fuel for AI and ML. But without the right quality and quantity of data powering the platform, these technologies can’t do their job effectively, or worse become destructive through inaccurate or harmful decisioning. By using AI and ML in technologies, companies create an adaptive layer, which drives both the breadth of use required to scale through partners and the depth of use that calls for a deep understanding of the technology.
The integration of AI and ML opens the possibilities for the application of the platform, broadening its use across different verticals and business cases. Using an adaptive AI engine, the same technology and data can be leveraged for multiple use cases. For example, a bank can monitor for financial crime as well as uncover new business opportunities from a single data environment.
While companies can go broad when looking at how AI and ML can impact the business, they also need to have a deep understanding of what AI and ML are doing within a platform. A strong partner is one who not only has the ability to broaden the use of AI across a company, but also has the knowledge to do it the right way. Leveraging the partner’s expertise in these specific areas becomes absolutely critical to making AI work effectively.
Unfortunately, the worId is littered with failed AI projects. When businesses and partners are not in control, or partners lose sight because there is not enough known outcome data or poorly categorized outcomes, the success of AI projects are often ineffective. Clients and partners need to inject subject expertise to guide the models. Like any project, failed AI ventures have large cost implications alongside the high risk of reputational damage. A failed partnership is usually a lost partnership.
So how do AI/ML technology firms ensure they are choosing the right partner for their needs? One strategy is to look at where the partner decides to scale out and deep. Not all partners have capacity to scale for breadth, but by selecting partners geographically and at a use case level focuses the selection to ensure success. Being clear with your partners about team structure, type of resource and level of experience, you ensure the effective delivery of projects. One way this could be achieved is by the technology vendor providing a training academy to equip partner staff with the level of expectation required.
Also, aim to evolve your strategic partners to the front-runners for all your sales. When approaching a partnership from this angle, companies have to be sure that their partnership is solid, meaning that they would trust their partner to bring them the same quality and amount of business that they would go after if they were making the pitch themselves. If a company is going to have a partner marketing on their behalf, they must be enabled with the proper resources and understanding the AI application, as well as proven knowledge in the field so that customers feel as though they are working with the company itself.
It can be difficult to determine what type of partner may be best for scaling out a business. Technology firms with a heavy focus on AI and ML need to ensure that they choose a partner strategy that aligns with the importance of the data required when working with these technologies. Those partners that are able to bring value to the platform and fit in with the company’s long-term growth goals, is how AI and ML technology firms will be able to scale successfully.
About The Author
Mark McNerney is the Global Alliances Director at Quantexa, establishing and maintaining strategic relationships to drive business opportunity in international markets.