Accenture Technology launches AI testing services

22 February 2018 4 min. read

Accenture Technology has launched a new set of Artificial Intelligence Testing Services. As an increasing regulatory burden sees many organisations turning to AI to lighten their workload, the new Services will aim to test AI solutions to make sure they can provide clients with the most trust-worthy service.

Much was made of Accenture’s $1.8 billion acquisition plan last year, as the firm sought to grow into a number of new business lines. While the majority of the coverage was devoted to Accenture Interactive’s perceived challenge to the advertising industry, though, the organisation also made significant strides into the world of AI and technological solutions.

As Accenture prepared to meet an increased demand for such solutions, particularly relating to regulatory compliance, the firm’s Technology wing made a number of investments toward the end of 2017. This included the purchases of technology and systems integration firm VERAX and Investit, who were subsequently rebranded as Accenture’s ‘Investment Management Business Insights’ division.

Now, as 2018 sees the final implementation of a number of new financial sector regulations, GDPR being the most notable among them due to its huge potential fines, Artificial Intelligence (AI) is being spoken of as a potential time and money saver, as companies rush to meet stringent new compliance demands. Testing AI systems to ensure their effectiveness is therefore paramount, and in this context, Accenture Technology has launched new services for testing AI systems, powered by a unique “Teach and Test” methodology designed to help companies build, monitor and measure reliable AI systems within their own infrastructure or in the cloud.

Accenture AI Testing Services

Kishore Durg, Senior Managing Director for Growth and Strategy and Global Testing Services Lead at Accenture, said, “Testing AI systems presents a completely new set of challenges… There is also a need for new capabilities for evaluating data and learning models, choosing algorithms, and monitoring for bias and ethical and regulatory compliance. Accenture’s “Teach and Test” methodology takes all of this into consideration to help companies develop and validate AI systems with confidence.”

Teach and Test

Accenture’s “Teach and Test” methodology ensures that AI systems are producing the right decisions in two phases. The “Teach” phase focuses on the choice of data, models and algorithms that are used to train machine learning. This phase experiments and statistically evaluates different models to select the best performing model to be deployed into production, while avoiding gender, ethnic and other biases, as well as ethical and compliance risks.
During the “Test” phase, AI system outputs are compared to key performance indicators, and assessed for whether the system can explain how a decision or outcome was determined. It uses innovative techniques and cloud-based tools to monitor the system on an ongoing basis for sustained performance. For instance, a patent-pending normalisation technique uses a unique algorithm to test object recognition more quickly.

Successful AI implementations require more than technology

Accenture AI Testing is part of a complete range of testing services aimed at helping engineering professionals to be catalysts of speed, agility and business performance, while achieving spikes in productivity. Accenture serves over 1,000 testing clients across more than 40 industries, and has already used its “Teach and Test” methodology to train a conversational virtual agent for a financial services company’s website, so that it could engage in accurate, unbiased conversations and know when to refer conversations to a human. The agent was trained 80% faster than previously possible, and achieved an 85% accuracy rate on customer recommendations.

“The adoption of AI is accelerating as businesses see it’s transformational value to power new innovations and growth,” Bhaskar Ghosh, Group Chief Executive for Accenture Technology Services said. “As organisations embrace AI, it is critical to find better ways to train and sustain these systems – securely and with quality – to avoid adverse effects on business performance, brand reputation, compliance and humans.”