The biggest question associated with the AI value chain remains – which will make money out of the entire value chain. Startups are struggling to win the race to achieve successful AI adoption.

While technology innovator startups are offering new products and cutting edge services,   the AI value chain market is dominated by technology giants such as Google, Microsoft, and Amazon.

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The enterprise software industry has been dominated by big names for decades. Now, startups are rushing to offer the next generation of such enterprise services, also attempting to disrupt the existing enterprise solutions even if they are too expensive, cumbersome, and complicated for them.

Whatever AI firms are hoping to achieve, the tech-giants will make sure to empower their organization with even more sophisticated AI hardware, cloud, and solutions. Startups need to smartly tackle the situation, and work against these brands to gain a foothold in the AI value chain.

The giants who want to stay at the forefront are investing in agile startups to get them there. To be associated with the big players, startups will need to offer them some level of assurance that their size or compliance ability will not be a risk such cooperation between startups and the leading tech-giants can deliver the best results for the AI industry. The best example of this is Salesforce investing in startups like -DigitalGenius, a customer management solution, and Unbabel, offering enterprise translation services. Following it, Salesforce also acquired Datorama, an AI-powered marketing company, for a rumored $800M.

SAP is also strategizing on similar lines as it acquired Recast.AI to accelerate its natural language processing capabilities for conversational agent technologies.

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Other than such mergers, AI startups are also making their presence felt by creating path-breaking industry-specific solutions. For instance, BenevolentAI has raised over $200M to power its moonshot to accelerate the creation of medicines using advanced data analysis. Across industries like healthcare, finance, automotive, legal, agriculture, industrials vast amount of money is being raised by startups to solve the most critical problems prolonged for years.

Multiple factors are responsible for successful AI startups.  They are succeeding maybe because they have access to proprietary data training sets, or better domain knowledge- assuring deeper insights into the opportunities available within a sector. The US venture capital market reported that funding for AI grew up to 72% that sums up to a whopping $9.3B in 2018. Successful AI startups have clearly understood the potential and the nature of AI technology, and how it is purchased and consumed. But, they are still struggling with minor hurdles like skills.

As reported by Gartner, enterprises are expected to derive a stupendous $3.9 trillion from all the AI use cases by 2022. These figures clearly indicate that most AI startups need to focus on providing enterprise solutions – horizontal solutions working across industries, or customized AI solutions for a specific industry.

All successful AI startups have crossed the technology and culture divide, broadening their vision and growth plans. The startups that are doing well understand AI and challenges associated with using it. They also know how to tackle those challenges to leverage AI to gain a competitive advantage. In such an increasingly competitive market, startups need to adopt smart business strategies to create their identity in the AI value chain amongst all the big tech-giants.

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