Everyone seems desperate to deploy some form of Artificial Intelligence (AI) in their businesses but most of them aren’t sure how to do it. The desperation is such that some companies even want to bypass traditional analytics and jump straight to AI. For the uninitiated, this is not an option. All businesses must embrace analytics completely before diving into AI. Whether you like it or not, AI is a journey. And, it’s a marathon, not a sprint. It would be safe to say, where analytics stops, AI begins.
As per insights from Forbes and Cowen & Company, 81% of IT leaders are currently investing in or planning to invest in AI. Based on the study, CIOs have a new mandate to integrate AI into IT technology stacks. The study found that 43% are evaluating and doing a Proof of Concept and 38% are already planning to invest more.
With $1.7 billion invested in AI startups in Q1 of 2017 alone and the exponential efficiencies created by this technology, the AI revolution will happen faster than what most business leaders are prepared for. So, the challenge is, how do you make your organisation AI ready?
In his book “AI and Analytics – Accelerating Business Decisions”, Sameer Dhanrajani, Chief Strategy Officer at Fractal Analytics shares four ways to prepare your organisation towards AI.
- You can acquire or invest in an innovative technology company applying AI/ML in your market, and gain access to new product and AI/ML talent.
- You can seek to invest as a limited partner in a few early stages AI-focused VC firms, gaining immediate access and exposure to vetted early-stage innovation firms, a community of experts and market trends.
- You can set out to build an AI-focused division to optimise your internal processes using AI, and map out how AI can be integrated into your future products. But recruiting in the space is tough and you will need a strong vision and sense of purpose to attract and retain the best.
- You can use outside development for hire shops like the new entrant Element.ai, who raised over $100 million last June, or more traditional consulting firms to fill the gaps or get the ball rolling.
Process-Based Focus Rather than Function Based
Dhanrajani says that strategy is the core element that differentiates success and failure in AI. “AI cannot be implemented piecemeal. It must be part of the organisation’s overall business plan along with aligned resources, structures and processes. How a company prepares its corporate culture for this transformation is vital to its long-term success.”
The preparation includes building a senior management and team that understands the benefits of AI, fostering the right skills, talent and training, managing change, and creating an environment with processes that welcomes innovation before, during and after the transition.
Tackling Resistance to Change by Top Management
“One of the biggest challenges to organisational (including digital) transformation is resistance to change,” Dhanrajani says. As per a survey, the maximum resistance in AI implementation often comes from the C-suite as there is such a lack of understanding about the benefits. They fail to realise that not implementing AI will adversely affect their bottom line and even cause them to go out of business.
Regulatory uncertainty about AI, rough experiences with previous technological innovation and a defensive posture to better protect shareholders— not stakeholders—may be the contributing factors.
Pursuing AI without senior management support is difficult. This is corroborated by statistics shared in the book which suggests that most of the leading AI companies (68%) strongly agree that their senior management understands the benefits AI offers. By contrast, only 7% of laggard firms agree with this view. Curiously though, the leading group still cites the lack of senior management vision as one of the top two barriers to the adoption of AI.
Reskilling and HR Redeployment
AI has often been criticised by a section of the people for leading to job loss. “But AI also creates numerous job opportunities in new and different areas, often enabling employees to learn higher level skills. In healthcare, for example, physicians are learning to work with AI-powered diagnostic tools to avoid mistakes and make better decisions. The question is who owns the data. If HR retains ownership of people data, it continues to have a role. If it loses that, all bets are off,” Dhanrajani says.
HR’s other role in an AI future will be to help make decisions about if and when to automate, whether to reskill or redeploy the human workforce and the moral and ethical aspects of such decisions. Companies experimenting with bots and AI, and with no thought given to the implications, need to realise that HR should be central to the governance of AI automation.
Given the potential of AI to complement human intelligence, it is imperative for top-level executives to be educated about reskilling possibilities. It is in the best interest of companies to train workers who are being moved from jobs that are automated by AI to jobs where their work is augmented by AI.
The Process of Supporting Innovation
Besides developing capabilities among employees, an organisation’s culture and processes must also support new approaches and technologies. Innovation must be embedded in the culture of the organisation and it often takes longer than expected because of the human element. The trick is to identify and drive visible examples of adoption.
As far as adoption is concerned, algorithmic trading, image recognition/tagging and patient data processing are predicted as top AI uses cases by 2025. Market intelligence firm Tractica forecasts that predictive maintenance and content distribution on social media will be the fourth and fifth highest revenue-producing AI uses cases over the next 8 years.
AI in the Indian Context
AI in India is at a nascent stage but at the cusp of rapid change. In an exclusive chat with The Startup Observer, Dhanrajani says that in India, it is still a phase of AI 1.0 which includes only text, media, voice, and image. We need to move to AI 2.0 which involves going beyond these basic elements to solving more complex problems by integrating newer technologies such as IoT and blockchain. Finally, we need to evolve to AI 3.0 which is mimicking the human brain. India is at an advantage from the point of view that many companies already have a strong repository of analytics and it’s just a matter of time that we catch up. This is indeed an opportunity for India to stay ahead of the AI curve.
(Editor’s note: The article has been largely inspired by one of the chapters in Sameer Dhanrajani’s book titled “AI and Analytics – Accelerating Business Decisions”. The book is strongly recommended for all AI decision makers.)