Artificial Intelligence: Harnessing Opportunities to Win in Future
Artificial intelligence (AI) is the new gear in the industry. The AI is expected to deliver increased productivity, faster service, generate innovative perspectives, insights and discover new ways to outperform rivals. Despite the potential and promises of AI, few reports have indicated that it is far more challenging to implement that it was expected. Over ambitious AI projects may face set back or not deliver the desired results and in turn the whole AI venture may not look appealing from ROI viewpoint. But the game changing elements that AI has cannot be brushed aside. With the right value pool and velocity AI can be one of the most important device for a sustained competitive advantage in the future. Let’s explore the terrain.
Project automation selection is structured for maximizing the efficiency scope by selecting a huge team that operates manually. In scenarios like this team handles hundreds of different customers with their own requirements and customization at various levels. There are multiple sources of data inputs in various formats. There are few steps which can’t be automated and it requires multiple interventions. Because of the complexity and cost pressure projects are abandoned and instead integration projects are run to fix it.
Scorecards may be used to categorize process and projects on the basis of the cost of developing the solutions, technical feasibility, economic feasibility, dynamics of human capital complexities, adoption and acceptance resulting in the grids of Fast Wins, Insight Builder & Comprehensive Transformation.
Fast wins are the low hanging fruits which can be grabbed by Robotic Process Automation (RPA’s). The repetitive routine tasks performed by knowledge workers are moved to RPA bots which expands value by completing tasks faster. The RPA’s accelerate time to value, reduce human error and increase throughput. This domain includes the work as copy and pasting the same data into multiple systems, Email Automation, Report generation and distribution, automated file transfers, etc.
Insight Builder are the machine learning applications which handle large volume of data and involve high speed number crunching that would go beyond human capability. Here advanced analytics majorly represent machine learning (ML) algorithm which works on large data sets to make predictions and recommendations. AI can handle both linear and non linear problems. This opens a plethora of optimization opportunities. These ML applications are used for personalizing ads, predict customer choices and buy, credit card fraud detection in real time, supply chain management.
Comprehensive Transformation are the projects with human -like engagements. These are the ones which engages customers and employees as intelligent agents and interact with them as a help desk. This category uses natural language processing chatbots, advanced ML, computer vision. The chatbots addresses broad range of topics but they are very basic in nature. Many of the companies are using it as internal bots for answering to employees on HR policy, employee benefits, basic requests like status on ticket status. Few companies are also using it to transform the user experience with consumption tailoring like engagement apps on mobile.
Changing Industry Structure and AI as tool for Competitive Advantage
The change in the external environment is imperative and the dynamics are changing and boundaries are pushed. The adoption of AI as a tool for competitive advantage needs multi- lens approach.
Winning in Medium Term: When the stakes are huge an honest assessment is required to be done by the company. In next few years what is the ambition plan. The changes in the operative model desired by the adoption of AI should be outlined on how the new business models will be structured. A mix of Fast Win RPA’s, Insight Builder’s and comprehensive transformation projects can be taken up. Confidence should be pumped by successful deployment of RPA+AI projects which are easy to deploy, accept and integrate in the system. Release funds and free up resources for insight builders and create road map for transformative journey. Set clear and considered expectations.
Organizational Acceptance: Successful AI adoption requires strong C-suite leadership support. Successful AI implementers design and adjust the firmwide strategy around the adoption and implementation of the AI. This is critical as the automation strategy should work in close tandem with other strategic priorities and complement rather than conflict with the firm’s strategy.
Optimizing Human- Machine Interface: Once powerful insights are produced; they must be integrated in the business system to capture the benefits. This may involve process redesign to embrace the changes in the workflow. Optimization of the human- machine interaction is very critical on determining what tasks should be automated and what will be in under human hand. Proper cognizance and rigor must be followed to optimize human – machine interface.
Building AI Ecosystem: Having a strong and upgraded technology is at the core of AI. The organization should focus on building or acquiring the necessary technological capability. Massive computing, processing power, data storage, strong networking infrastructure are key constituents. Adding to this is right kind of talent pool hired and retained. Gear up the enterprise to operate in agile environment.
Investing in Change Management: Process team’s best people work with the project team, pour in hours explaining the process work flow, requirements and deliverables. Despite spending hours, they don’t get the clear-cut answer on what will be changes and how the different tools will work together. There is no defined policy on how to train the staff into the new way of working. As AI implementation may take substantial amount of time to implement, frustrations set up with the process team as no clear out put is there on the table. Worse at times automation does not perform the said results and team has to go back into manual mode. Automation plans are highly disruptive, creates confusion and distrust in ranks. Organization must have a plan to navigate and positively absorb the changes brought in by AI.
Dislodge Uncertainties and Fear: There is a general fear that AI will replace people out of work. However, RPA’s perform the monotonous, repetitive tasks allowing employees to perform high value tasks. Whereas insights builder are deep learning and high velocity number crunching which is beyond the human capability. The insight builder no way possesses any threat on the contrary because of distinctive insights generated, better and more opportunities surfaces for human to explore. Whereas transformative projects are still in immature because of which many companies are taking conservative approach. Currently the artificial agents deployed 24X7 addresses the basic issues and beyond that they pass prebuilt information to the human to address the complex queries. People as a part of strategy, massive reskilling and capability building exercise has to be taken across organization to upgrade the value skills.
There is no substitute for action. It’s time to think beyond tomorrow. AI is going to transform the way business is conducted. Strategize AI to win in future. NOW is the time for action.
