Healthcare Artificial Intelligence (AI) is a challenging field to enter, with a lack of widespread commercial success. This is not the case with other industries such as Financial Services which has seen ventures into AI go from strength to strength. Why, given the relative transferability of the technologies, have we not seen widespread successful implementations in Healthcare and the NHS? More importantly, how do we get it right going forward? The regulatory environment for Healthcare is complex and ever-evolving.

BOSTON--(BUSINESS WIRE)--Today, Neurala, the leader in vision AI software, announced that it has raised $12 million in funding to advance the development of vision AI for manufacturing. The round, led by Zebra Ventures and Pelion Venture Partners, with participation from Draper Associates, Friulia, AddValue, 360 Capital Partners, Idinvest Partners, Cougar Capital, and industrial investors IMA and Antares Vision, brings the total invested in Neurala to $26 million. The funding will enable Neurala to evolve and accelerate adoption of its vision AI in the industrial and manufacturing sectors on a global scale, as manufacturers increasingly prioritize automation as part of Industry 4.0 initiatives. Neurala is a pioneer in vision AI for manufacturing. Built on the company's deep AI expertise, Neurala's VIA software delivers an integrated solution designed to help manufacturers improve quality inspection on the production line.

A few months ago, countries closed their borders, economies ground to a near standstill, employees became remote workers overnight, and everything we knew about doing business changed. Even today, we hear about "the new normal", "the great reset", and organizations are still required to demonstrate high agility to adapt in sudden changes in their market and region. For many organizations, global crises have historically represented a watershed moment. Those that adapt and pivot are able to turn adversity into advantage, whereas those that don't, risk failure. In this sense, COVID-19 is no different – accelerating several major business trends that were well underway before the outbreak began while forcing others to become obsolete.

Failure to Scale Artificial Intelligence Could Put 75% of Organizations Out of Business, Accenture Study Shows Companies that shift from AI experimentation to execution achieve lasting ROI and competitive agility NEW YORK; Nov. 14, 2019 – Three-quarters of C-level executives believe if they don't move beyond experimentation to aggressively deploy artificial intelligence (AI) across their organizations they risk going out of business by 2025, according to a newly released study from Accenture (NYSE: ACN). The report, titled "AI: Built to Scale" and produced by Accenture Strategy and Accenture Applied Intelligence, is based on a global survey of 1,500 C-level executives across 16 industries designed to understand how companies are implementing AI across their organizations. The research found 84% of C-level executives believe they won't achieve their business strategy without scaling AI, yet only 16% have made the shift from mere experimentation to creating an organization powered by robust AI capabilities. As a result, this small group of top performers is achieving nearly three times the return from AI investments as their lower-performing counterparts. The report reveals the secret to success for these top performers centers around three key elements: a strong data foundation; multiple dedicated AI teams; and a C-suite-led commitment to strategic, organization-wide AI deployment.

Artificial intelligence (AI) capabilities are on the precipice of revolutionizing the way we work, reshaping businesses, industries, economies, the labor force, and our everyday lives. We estimate AI-powered applications will add $13 trillion in value to the global economy in the coming decade, and leaders are energizing their agendas and investing handsomely in AI to capitalize on the opportunity--to the tune of $26 billion to $39 billion in 2016 alone. Meanwhile, AI enablers such as data generation, storage capacity, computer processing power, and modeling techniques are all on exponential upswings and becoming increasingly affordable and accessible via the cloud. Conditions seem ripe for companies to succeed with AI. Yet, the reality is that many organizations' efforts are falling short, with a majority of companies only piloting AI or using it in a single business process--and thus gaining only incremental benefits.